Embedded Image and Vision Processing 2017 report by Yole Developpement

FromTechnologies to Market
From image
processing to deep
learning,
introduction to
hardware and
software
2017 Report
Sample
November 2017

2
Biographies and Contacts
ABOUT THE AUTHORS
As a Software & Market Analyst, Dr. Yohann Tschudi is a member of the MEMS & Sensors business unit at Yole Développement
(Yole). Yohann is daily working with Yole’s analysts to identify, understand and analyze the role of the software parts within any
semiconductor products, from the machine code to the highest level of algorithms. Market segments especially analyzed by
Yohann include big data analysis algorithms, deep/machine learning, genetic algorithms, all coming from Artificial Intelligence (IA)
technologies.
After his thesis at CERN (Geneva, Switzerland) in particle physics, Yohann developed a dedicated software for fluid mechanics
and thermodynamics applications. Afterwards, he served during 2 years at the University of Miami (FL, United-States) as a
research scientist in the radiation oncology department. He was involved in cancer auto-detection and characterization projects
using AI methods based on images from Magnetic Resonance Imaging (MRI). During his research career, Yohann has authored and
co-authored more than 10 relevant papers. Yohann has a PhD in High Energy Physics and a master degree in Physical Sciences
from Claude Bernard University (Lyon, France).
Email: tschudi@yole.fr
YohannTschudi
©2017 | www.yole.fr | From image processing to deep learning, introduction to hardware and software

3
TABLE OF CONTENTS
REPORT OBJECTIVES AND METHODOLOGY 5
1 – INTRODUCTION 12
Software
Embedded software
2 – IMAGE PROCESSING 23
Definition
Basics : Primary ISP architecture for Bayer image sensor
Image processing to recover artefacts
Image processing for color reproduction
Image processing with pre-/post-processing
Conclusion
3 – ARTIFICIAL INTELLIGENCE 42
Definition
A modern history of AI
AI technologies
Discussion
4 – PLAYERS AND MARKET DYNAMICS 59
ISP & vision processor
AI in vision systems
CONCLUSIONS 87

4
Dual cameras
Video stabilization
HDR
Super resolution
Digital zoom
Deep learning
AR/VR
SLAM
Video analytics
3D reconstruction
Forward collision warning
Lane departure
Pedestrian detection
Traffic sign detection
Free space
Gesture recognition
Behavior recognition
Eye tracking
Iris recognition
Face recognition
Face detection
Computational
photography
Machine visionAutomotive
Human machine
interface
SCOPE OF THE REPORT
2 domains are
considered in
this report
Image signal processor
and vision processor
Artificial intelligence in
vision systems
Technologies
L
e
n
s
Image
sensor
Demosaicin
g
Noise filter
for luma
Color
space
conversion
Noise filter
for chroma
Data
formatter
Gamma
correction
Color
correction
White
balance
Hue
saturation
control
Dead pixel
concealme
nt
Black level
compensati
on
Lens
shading
correction
Edge
enhanceme
nt
Contrast
brightness
control
Not shaded
technologies are not
treated in this report

5
Algolux,Altek,Ambarella,AMD,ARM,Apple, CEVA, Canon, Chips&Media, DNNresearch, DeepMind, Emotient,
Fotonation, Google, Intel, Imagination, Lattice, Microsoft, Mobileye, Movidius, Nextchip, Nvidia, NXP, Omnivision,
ON Semiconductors, Pixelworks, Qualcomm, Realface, Socionext, Sony, STMicroelectronics, Sunplus, Synopsys,
Xperi
COMPANIES CITED IN THIS REPORT

6
SOFTWARE
General
definition
Analogy
Set of sequences of instructions (programs) that can be interpreted by a machine and a set of data necessary for these operations
Hardware Software

7
SOFTWARE LICENSE
Type of
licensing for
software
Public
domain
Non
protective
FOSS*
license
Protective
FOSS*
license
Proprietary
license
Trade
secret
More rights granted Less rights granted
*Free and Open Source Software
Freeware
Shareware
Freemium
Copyright
retained
No Yes Yes Yes Yes Yes
Perform and
display
Yes Yes Yes Yes Yes No
Copy Yes Yes Yes Often No No
Modify Yes Yes Yes No No No
Distribute Yes
Yes, under same
license
Yes, under same
license
Often No No
Sublicense Yes Yes No No No No
Examples
SERVER-SIDE
The Google search
algorithm

8
EMBEDDED SOFTWARE
Global
definition
• Embedded software is used to control the limited and set functions of hardware devices. It is not typically worked
with directly by users. Its functions are activated by external controls, either external actions of the device itself or
remote input. The device may have communication links to other devices for functionality or in case the device
needs to be adjusted, calibrated or diagnosed.
• It is written specifically for the particular hardware that it runs on and usually has processing and memory
constraints because of the device’s limited computing capabilities. Examples of embedded software include those
found in dedicated GPS devices, factory robots, some calculators and even modern smartwatches.
• Embedded software varies in complexity as much the devices it is used to control. Although the term is often used
interchangeably with firmware, embedded software is often the only computer code running on a piece of hardware,
while firmware, in contrast, hands over control to an operating system that in turn launches and controls programs.
• In this report we will focus on two types of embedded software in vision systems :
Image processing
Very close to hardware
Inference software from AI’s
technics
High level algorithms

9
IMAGE PROCESSING PIPELINE
ISP blocks
details
L
e
n
s
Image sensor
Demosaicing
Noise filter for
luma
Color space
conversion
Noise filter for
chroma
Data formatter
Gamma correction Color correctionWhite balance
Hue saturation
control
Dead pixel
concealment
Black level
compensation
Lens shading
correction
Edge enhancement
Contrast brightness
control

10
ISP &VISION PROCESSOR MARKET SHARES AND EVOLUTIONS
Some clues on
what
happening for
the hardware
segment
IP and
hardware

11
AI INVISION SYSTEMS
Focus on AI
technologies
in vision
systems
• The main goal of AI is for an artificial system to be autonomous. For that, understanding the environment an navigate
through it takes a large part of the research.
• Because 80% of the human understanding of the world pass through eyes, vision systems share with AI one main
research topic :

12
DEEP LEARNING
The most
powerful
method in
vision systems
• Deep learning is part of machine learning methods.
• It is based on deep neural networks which are ANN with multiple hidden layers between the input and output
layers.
• In computer vision, DL is used for object recognition. Although CNNs trained by backpropagation had been around
for decades, and GPU implementations of ANNs for years, including CNNs, fast implementations of CNNs with
max-pooling on GPUs and high level memory were needed to progress on computer vision.
Example of DNN used
for face recognition
during the training phase

13
AI RELATED TOVISION SYSTEMS GLOBAL CHARACTERISTICS
Main
characteristics
of the
embedded
inference
software
technologies
in vision
systems
High
Medium
Low
Not relevant
Image
processing
Face
detection
Eye tracking
Iris
recognition
Face
recognition
Object
detection
Free space
recognition
Gesture
recognition
Object
recognition
Behavior
recognition
CPU
requirements
Memory
requirements
Resolution
requirements
Execution
speed
requirements
Algorithm
complexity
Training
requirements
Range <10m <1m <1m <1m <100m <3m <3m <50m 5-20m
Learn in usage Yes Yes No Yes No No No No No
Input from
Photo (P) or
Video (V)
P/V P V P P V V V V V
Very high
Object analysis Scene analysis

14
EMERGENCE OF AI – TECHNOLOGICAL FACTORS
Technological
factors implied
in the
emergence of
AI in vision
systems and
forecast

15
RELATED REPORTS

Vision systems are becoming increasingly
important. Therefore, this report shows and
explains the close links between embedded
software and hardware in vision systems at the
technology and market levels. What are the
software technologies? How do they impact
the hardware? Which hardware is impacted?
What kinds of markets are affected? And how
will they evolve?
We can consider software in vision systems
as having two different levels. The first is
very close to the hardware, inscribed inside
standalone field programmable gate array
(FPGA) or application specific integrated
circuit (ASIC) chips, or integrated into more
complicated architectures. This layer, not
often considered, is the most important step
in any image treatment after image acquisition
by pixels. Image processing, realized in the
image signal processor (ISP), has a quite
simple function. It must transform a signal
from the sensor to an understandable image
for the human eye. It is composed as a pipeline
of multiple blocks, where each block takes as
input the output of the previous block. A lot
of different algorithms are implemented to
accomplish tasks such as removing artefacts,
color correction and reproduction. This is
done at a single-pixel or pixel-group level and
does not need a lot of memory or power.
The second software layer is completely
different, with much more diverse and
complicated functions. In this report, we
focused on embedded software and, more
precisely, inference software derived from
the latest artificial intelligence (AI) methods.
This kind of technology necessitates a lot
of memory and computing power. It uses
complete image frames as input, and its goal is
not to correct, but to analyze and understand
the world in the picture. In vision systems,
AI technology focuses on detection of eyes,
faces, traffic signs, pedestrians, lanes, objects
in front of cars and free space, and recognition
of faces, irises, behaviors and gestures based
on a mathematical technique called a neural
network. This report especially investigates
one of the most famous technologies, which
has given spectacular results in recent years:
deep learning.
FROM IMAGE PROCESSING TO DEEP LEARNING,
INTRODUCTION TO HARDWARE AND SOFTWARE
Market & Technology report - November 2017
SOFTWARE INVISION SYSTEMS
From algorithms included in the image processing pipeline to neural networks running in vision
processors, focus on the evolution of hardware in vision systems and how software disrupts this
domain.
KEY FEATURES OF THE REPORT
Get the sample of the report
on www.i-Micronews.com
• Image processing technology
description
• Description of Artificial Intelligence
(AI) technology in vision systems
• Intellectual property, hardware
and business models for the
image signal processor and vision
processor market
• AI technology and business models
in the vision system ecosystem
• Technology trends and future
outlook
(Yole Développement, November 2017)
Artificial intelligence technologies in vision systems
Computational
photography
Machine visionAutomotive
Human machine
interface
Dual
cameras Video
stabilization
HDR
Super
resolution
Digital
zoom
Deep
learning
AR/VR
SLAM
Video
analytics
3D
reconstruction
Forward
collision
warning
Lane
departure
Pedestrian
detection
Traffic sign
detection
Free space
Gesture
recognition
Behavior
recognition
Iris
recognition
Face
recognition
Face
detection
OBJECTIVES OF THE REPORT
Understand the technologies
• Image processing pipeline
• AI technologies based on neural
networks
Understand the evolution of
hardware
• Business models
• Image signal processor to vision
processors to sensor fusion
• Market share and evolution
Understand how software is
disrupting hardware and future trends
The shaded technologies are addressed in this report

FROM IMAGE PROCESSING TO DEEP LEARNING, INTRODUCTION TO HARDWARE AND SOFTWARE
HARDWARE MARKET AND BUSINESS MODELS
AI has completely disrupted hardware in vision
systems, and has had an impact on entire
segments, like Mobileye has in automotive, for
example. Image analysis adds a lot of value and
image sensor builders are therefore increasingly
interested in integrating a software layer to
their system in order to capture it. Today, image
sensors must go beyond taking images – they
must be able to analyze them.
However, to run these types of software, high
power computing and memory are necessary,
which led to the creation and development of
vision processors. The image signal processor
(ISP) market offers a steady compound annual
growth rate (CAGR) of 6.3%, making the total
market worth $4,400M in 2017. Meanwhile,
the vision processor market is exploding, with
a 30.7% CAGR and a market worth $653M in
2017!
Today, optimization requires software and
hardware to be developed in parallel. Depending
on the issues and specifications, companies can
invest more in hardware than software or vice
versa. However, software is easier to specify,
tune and update, and so its growth is more
important than hardware. The AI market is
therefore expected to reach $35B in 2025 with
an estimated CAGR at 50% per year from 2017-
2025.
This report carefully evaluates ISP and vision
processor market shares and their evolution
in order to correctly understand how AI
technology impacts the hardware. This market
has been divided in two different business
models: Intellectual Property (IP) companies,
which don’t have physical products, and
hardware companies, which sell the processors
physically. The leaders are pretty easy to identify
for each category. ARM and Synopsys lead the
IP segment and Omnivision, Mobileye and ON
Semiconductor lead the hardware segment.
The AI market, particularly in vision systems, is
new and still moving, with hundreds of startups
created each year. It has no clear leaders but a
lot of highly specialized companies. This report
therefore gives a high-level view of driving
forces, technology hype, and the most important
mergers and acquisitions.
The main goal of this report is to understand what
is happening with the emergence of AI. Even if it
is not a new technology, thanks to technological
factors AI has made a spectacular entry into vision
systems. It opens new perspectives in various
segments such as automotive, surveillance,
biometrics and medical. However, it also poses
ethical questions, which we have tried to answer.
AI technologies promise a bright future in
many areas, with rapid software and hardware
progress. In autonomous vehicles, AI allows cars
to understand the world around them, predict
trajectories, communicate and drive. This has led
to the development of sensor fusion boards. For
example, NVidia’s Drive PX boards provide very
high performance computing and memory, giving
the ability to compile information from many
completely different sensors. In surveillance and
security, face and iris recognition have never
been as powerful, entering the consumer world
through the iPhone X this year, and behavior
recognition is on track.
From image signal processor to sensor fusion processor
Hardware markets size evolution 2012-2021
Vision processor from Mobileye
Frame
processing
Vision processor
Amount of
data processed
Fully AI to reach
autonomy
Introduction of AI
algorithms
Is part of
Price
per
unit
$1000
$10
$1
Set of pixels
processing
ISP
Image processing
algorithms
Standalone ISP from Altek
Frame processing
+ other sensors
Sensor fusion processor
from NVidia
$
sion processorr
from NVidia
WHEN SOFTWARE DISRUPTS HARDWARE
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
Revenues(US$million)
Intellectual Property - Image signal processor Intellectual Property -Vision processor
Hardware -Vision processor Hardware - Image signal processor

MARKET TECHNOLOGY REPORT
Emergence of artificial intelligence - Technological factors
Find more
details about
this report here:
COMPANIES CITED IN THE REPORT (non exhaustive list)
Algolux, Amazon, Altek, Ambarella, AMD, ARM, Apple, B-Secur, Biowatch, CEVA, Canon,
ChipsMedia, Cognitec, Delta ID, Ergoneers, EyeLink, Eyesmart Technology, Eyetech,
Face++, Facebook, Fotonation, Google, IBM, Intel, Imagination, Irisys, Iritech, ISCAN, Kairos,
LC Technologies, LG, Microsoft, Mobbeel, Mobileye, Movidius, Nec, Nextchip, Nvidia, NXP,
Omnivision, ON Semiconductor, OpenCV, Parrot, Pixelworks, Princeton Identity, Qualcomm,
SensorMotoric Instruments, Smart Eye, Socionext, Sony, Sthaler, STMicroelectronics,
Sunplus, Synopsys, The Eye Tribe, Tobii, Xperi...And more.

Report objectives and methodology 5
Introduction12
Software
Embedded software
Image processing 23
Definition
Basics : Primary ISP architecture for
Bayer image sensor
Image processing to recover artefacts
Image processing for color reproduction
Image processing with pre-/post-
processing
Conclusion
Artificial intelligence 41
Definition
A modern history of AI
AI technologies
Discussion
Players and market dynamics 59
ISP and vision processor
AI in vision systems
Conclusions83
Company profile 90
TABLE OF CONTENTS (complete content on i-Micronews.com)
• 3D TSV and 2.5D Business Update - Market
and Technology Trends 2017
• 3D Imaging and Sensing 2017
• Status of the CMOS Image Sensor Industry
2017
RELATED REPORTS
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AUTHOR
Dr. Yohann Tschudi as a Software
Market Analyst, Dr. Yohann Tschudi is a
member of the MEMS Sensors business
unit at Yole Développement (Yole). Yo-
hann is daily working with Yole’s analysts
to identify, understand and analyze the
role of the software parts within any
semiconductor products, from the ma-
chine code to the highest level of algo-
rithms. Market segments especially ana-
lyzed by Yohann include big data analysis
algorithms, deep/machine learning, ge-
netic algorithms, all coming from Artifi-
cial Intelligence (IA) technologies.
After his thesis at CERN (Geneva, Swit-
zerland) in particle physics, Yohann de-
veloped a dedicated software for fluid
mechanics and thermodynamics appli-
cations. Afterwards, he served during
2 years at the University of Miami (FL,
United-States) as a research scientist in
the radiation oncology department. He
was involved in cancer auto-detection
and characterization projects using AI
methods based on images from Magne-
tic Resonance Imaging (MRI). During his
research career, Yohann has authored
and co-authored more than 10 relevant
papers.
Yohann has a PhD in High Energy Physics
and a master degree in Physical Sciences
from Claude Bernard University (Lyon,
France).
Find all our reports on www.i-micronews.com
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
2008 2010 2012 2014 2016 2018 2020
Amount of data stored
$0,01
$1
$100
$10 000
$1 000 000
$100 000 000
$10 000 000 000
$1 000 000 000 000
1950 1960 1970 1980 1990 2000 2010 2020
IBM 7030
Stretch
Cray X-MP/48
Beowulf
cluster
KASY0
Approximate cost per GFLOPS
(109
operations per second)
(Exabytes – 1018
bytes)
Estimated
Al is very exciting for the entire area of vision systems. This report tries to show why it is
important to understand the technologies and their impacts, and how to react. AI is in vision
systems, from technology to market.

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− Piezo MEMS 2018 *
o PATENT ANALYSES – by KnowMade
− MEMS Microphone – Patent Landscape Analysis
− Knowles MEMS Microphones in Apple iPhone 7 Plus – Patent-to-Product
Mapping 2017
o LINKED REPORTS – by Yole Développement, System Plus Consulting and KnowMade
− MEMS Pressure Sensor 2018 – Market Technology Report
− MEMS Pressure Sensor Comparison 2018 – Structure, Process Cost Report
− Gas Particles 2018 – Market Technology Report
− Gas Particles Comparison 2018 – Structure, Process Cost Report
− LiDARs for Automotive and Industrial Applications 2018 – Market
Technology Report
− LiDAR for Automotive 2018 – Patent Landscape Analysis
− MEMS Packaging 2017 – Market Technology Report
− MEMS Packaging Comparison 2017 – Structure, Process Cost Report
RF DEVICES ANDTECHNOLOGIES
− Wireless technologies (Radar, V2X) for Automotive 2018
− RF Standards and Technologies for Connected Objects 2018
− RF Photonic Components Technologies for 5G Infrastructure2018
o REVERSE COSTING® – STRUCTURE, PROCESS COST REPORT– by System
Plus Consulting
− Automotive Radar Comparison 2018
− RF Acoustic Wave Filters 2017 – Patent Landscape Analysis
o LINKED REPORTS – by Yole Développement, System Plus Consulting andKnowMade
− 5G impact on RF Front End Modules and Connectivity for Cellphones 2018 – Market
Technology Report – Update
− RF Front-End Module Comparison 2018 – Structure, Process Cost Report
− RF Front End Modules for Cellphones 2018 – Patent Landscape Analysis
− Advanced RF System-in-Package for Cellphones 2018 – Market Technology
Report – Update*
− Advanced RF SiPs for Cell Phones Comparison 2017 – Structure, Process
Cost Report
− RF GaN Market: Applications, Players, Technology, and Substrates 2018-2023
Market Technology Report – Update
− RF GaN Comparison 2018* – Structure, Process Cost Report
− RF GaN 2018 – Patent Landscape Analysis
SOFTWARE
− Consumer Biometrics: Sensors Software 2018 – Update
− Processing Hardware and Software for AI 2018 - Vol. 1 2
− From Image Processing to Deep Learning, Introduction to Hardware and Software
Update : 2017 version still available / *To be confirmed

IMAGING OPTOELECTRONICS
− Status of the Compact Camera Module and Wafer Level Optics
− Industry 2018 – Update
− 3D Imaging and Sensing 2018 – Update
− Sensors for Robotic Vehicles 2018
− Machine Vision for Industry and Automation 2018
− Imagers and Detectors for Security and Smart Buildings 2018
− Uncooled Infrared Imagers 2017
− iPhone X Dot Projector – Patent-to-Product Mapping
− Status of the CMOS Image Sensor Industry 2018 – Market Technology Report -
Update
− CMOS Image Sensor Comparison 2018 – Structure, Process Cost Report
− CMOS Image Sensors Monitor 2018* – Quaterly Update**
− Camera Module 2017 – Market Technology Report
− Compact Camera Module Comparison 2018 – Structure, Process Cost Report
− LiDARs for Automotive and Industrial Applications 2018 – Market Technology
Report
− LiDAR for Automotive 2018 – Patent Landscape Analysis
ADVANCED PACKAGING
− Status of Advanced Packaging Industry 2018 – Update
− Status of Advanced Substrates 2018: Embedded Die andInterconnects,
Substrate Like PCB Trends
− 3D TSV and Monolithic Business Update 2018 – Update
− Power Modules Packaging 2018 – Update
− Discrete Power Packaging 2018 – Update*
− Status of Panel Level Packaging 2018
− Trends in Automotive Packaging 2018
− Hardware and Software for AI 2018 - Vol. 1 2
− Integrated Passive Devices (IPD) 2018
− Thin-Film Integrated Passive Devices 2018
− Memory Packaging Market and Technology Report 2018 – Update*
− Hybrid Bonding for 3D Stack – Patent Landscape Analysis
o LINKED REPORTS– by Yole Développement and System Plus Consulting
− Advanced RF System-in-Package for Cellphones 2018 – Market Technology Report -
Update*
− Advanced RF SiPs for Cell Phones Comparison 2017 – Structure, Process
Cost Report
− Fan-Out Packaging 2018 – Market Technology Report – Update*
− Fan-Out Packaging Comparison 2018* – Structure, Process Cost Report
MANUFACTURING
− Wafer Starts for More Than Moore Applications 2018
− Equipment for More than Moore: Technology Market Trends
for Lithography Bonding/Debonding 2018
− Polymeric Materials for wafer-level Advanced Packaging 2018
− Laser Technologies for Semiconductor Manufacturing 2017
− Glass Substrate Manufacturing in the Semiconductor Field 2017
− Equipment and Materials for Fan-Out Packaging 2017
− Equipment and Materials for 3D TSV Applications 2017
o LINKED REPORTS – by Yole Développement and System Plus Consulting
− Equipment for More than Moore: Technology Market Trends for
Lithography Bonding/Debonding 2018 – Market Technology Report
− Wafer Bonding Comparison2018 – Structure, Process Cost Report

MEMORY
− Emerging Non Volatile Memory 2018 – Update
− Memory Packaging Market and Technology Report 2018 – Update*
o QUARTERLY UPDATE – by Yole Développement**
− Memory Market Monitor 2018 (NAND DRAM)
o MONTHLY UPDATE – by Yole Développement**
− Memory Pricing Monitor 2018 (NAND DRAM)
o REVERSE ENGINEERING COSTING REVIEW – by System Plus Consulting
− DRAM Technology Cost Review 2018
− NAND Memory Technology Cost Review 2018
− 3D Non-Volatile Memories – Patent Landscape
COMPOUND SEMICONDUCTORS
− Status of Compound Semiconductor Industry 2018*
− GaAs Materials, Devices and Applications 2018
− InP Materials, Devices and Applications 2018
− Bulk GaN Substrate Market 2017
− Power SiC 2018: Materials, Devices, and Applications – Market Technology
Report – Update
− SiC Transistor Comparison 2018 – Structure, Process Cost Report
− Power SiC 2018 – Patent Landscape Analysis
− Power GaN 2018: Materials, Devices, and Applications – Market Technology Report
– Update
− GaN-on-Silicon Transistor Comparison 2018 – Structure, Process Cost Report
− Status of the GaN IP – Patent Watch 2018 Patent Activity 2017
− RF GaN Market: Applications, Players, Technology, and Substrates 2018-2023
– Market Technology Report – Update
− RF GaN – Patent Landscape Analysis
POWER ELECTRONICS
− Status of Power Electronics Industry 2018 – Update
− Discrete Power Packaging 2018 – Update*
− Power Electronics for Electric Vehicles 2018 – Update
− Integrated Passive Devices (IPD) 2018
− Wireless Charging Market Expectations and Technology Trends 2018
− Thermal Management Technology and Market Perspectives in Power
− Electronics and LEDs 2017
− Gate Driver 2017
− Power MOSFET 2017
− IGBT 2017
− Market Opportunities for Thermal Management Components in
Smartphones 2017
o LINKED REPORTS – by Yole Développement, System Plus Consulting
and KnowMade
− Power Modules Packaging 2018 – Market Technology Report – Update
− Automotive Power Module Packaging Comparison2018 – Structure,
Process Cost Report
− Power ICs Market Monitor 2018 – Quaterly Update**
− Power ICs Market Comparison 2018* – Structure, Process Cost Report
BATTERY AND ENERGY MANAGEMENT
− Li-ion Battery Packs for Automotive and Stationary Storage Applications 2018 –
Update
− Status of the Battery Patents – Patent Watch 2018 Patent Activity 2017
o LINKED REPORTS – by Yole Développement and KnowMade
− Solid State Electrolyte Battery 2018 – Market Technology Report
− Solid-State Batteries 2018 – Patent Landscape Analysis
Update : 2017 version still available / *To be confirmed / ** Can not be selected within an Annual Subscription offer

SOLID STATE LIGHTING
− IR LEDs and Lasers 2018: Technology, Industry and Market Trends – Update
− Automotive Lighting 2018: Technology, Industry and Market Trends – Update
− UV LEDs 2018: Technology, Industry and Market Trends – Update
− LiFi: Technology, Industry and Market Trends
− LED Lighting Module Technology, Industry and Market Trends 2017
− CSP LED Lighting Modules
− Phosphors Quantum Dots 2017 - LED Downconverters for Lighting Displays
− Horticultural Lighting 2017
o LINKED REPORTS – by Yole Développement and System Plus Consulting
− VCSELs 2018: Technology, Industry and Market Trends – Market Technology
Report
− VCSELs Comparison 2018 – Structure, Process Cost Report
DISPLAYS
− Quantum Dots and Wide Color Gamut Display Technologies 2018 – Update
− Displays and Optical Vision Systems for VR/AR/MR 2018
− MicroLED Displays 2018 – Market Technology Report – Update
− MicroLED Display – Patent Landscape Analysis
MEDTECH
− BioMEMS Non Invasive Emerging Biosensors: Microsystems for Medical
− Applications 2018 – Update
− Point-of-Need Testing Application of Microfluidic Technologies 2018 – Update
− Neurotechnologies and Brain Computer Interface 2018
− CRISPR-Cas9 Technology: From Lab to Industries 2018
− Ultrasound technologies for Medical, Industrial and Consumer 2018
− Inkjet Functional and Additive Manufacturing for Electronics 2018
− Liquid Biopsy: from Isolation to Downstream Applications 2018
− Chinese Microfluidics Industry 2018
− Scientific Cameras for the Life Sciences Analytical Instrumentation
Laboratory Markets 2018*
− Artificial Organ Technology and Market 2017
− Connected Medical Devices Market and Business Models 2017
− Status of the Microfluidics Industry 2017
− Organs-On-Chips 2017
− Solid-State Medical Imaging 2017
− Medical Robotics Market Technology Analysis 2017
− Microfluidic IC Cooling – Patent Landscape
− Circulating Tumor Cell Isolation – Patent Landscape
− OCT Medical Imaging – Patent Landscape
− Pumps for Microfluidic Devices – Patent Landscape 2017
− Microfluidic Technologies for Diagnostic Applications– Patent Landscape 2017
− FLUIDIGM – Patent Portfolio Analysis 2017
− Consumer Physics SCiO Molecular Sensor – Patent-to-Product Mapping 2017
− Organs-On-Chips 2017 – Market Technology Report
− Organ-on-a-Chip– Patent Landscape Analysis

OUR 2017 PUBLISHED REPORTS LIST (3/3)
OUR PARTNERS’ REPORTS
PATENT ANALYSES – by KnowMade
− Wireless Charging Patent LandscapeAnalysis
− RF Acoustic Wave Filters Patent LandscapeAnalysis
− NMC Lithium-Ion Batteries Patent LandscapeAnalysis
− Pumps for Microfluidic Devices Patent Landscape
− III-N PatentWatch
− FLUIDIGM Patent Portfolio Analysis
− Knowles MEMS Microphones in Apple iPhone 7 Plus Patent-to-Product Mapping 2017
− Consumer Physics SCiO Molecular Sensor Patent-to-Product Mapping
− Patent Licensing Companies in the Semiconductor Market - Patent Litigation Risk and Potential Targets
− Microfluidic Technologies for Diagnostic Applications Patent Landscape
TEARDOWN REVERSE COSTING – by System Plus Consulting
More than 60 teardowns and reverse costing analysis and cost simulation tools published in 2017
MORE INFORMATION
o All the published reports from theYole Group of Companies are available on our website www.i-Micronews.com.
o Ask for our Bundle Subscription offers: With our bundle offer, you choose the number of reports you are interested in and select the related offer. You then haveup
to 12 months to select the required reports from the Yole Développement, System Plus Consulting and KnowMade offering. Pay once and receive the reports
automatically (multi-user format). Contact your sales team according to your location (see the last slide).

MICRONEWS MEDIA
o About Micronews Media
To meet the growing demand for market,
technological and business information,
Micronews Media integrates several tools able
to reach each individual contact within its
network.We will ensure you benefit from this.
ON L IN E ON SITE IN PERSON
@Micronews e-newsletter
i-Micronews.com
i-Micronewsjp.com
FreeFullPDF.com
Events Webcasts
Unique, cost-effective ways
to reach global audiences.
Online display advertising
campaigns are great strategies
for improving your
product/brand visibility.They
are also an efficient way to
adapt with the demands of the
times and to evolve an effective
marketing plan and strategy.
Brand visibility,networking
opportunities
Today's technology makes it
easy for us to communicate
regularly, quickly,and
inexpensively – but when
understanding each other is
critical, there is no substitute
for meeting in-person.Events
are the best way to exchange
ideas with your customers,
partners, prospects while
increasing your brand/product
visibility.
Targeted audience
involvement equals clear,
concise perception of your
company’s message.
Webcasts are a smart,
innovative way of
communicating to a wider
targeted audience.Webcasts
create very useful,dynamic
reference material for
attendees and also for
absentees, thanks to the
recording technology.
Benefit from the i-Micronews.com
traffic generated by the 11,200+
monthly unique visitors, the
10,500+ weekly readers of
@Micronew se-newsletter
Several key events planned for
2018 on different topics to
attract 120 attendees on average
Gain new leads for your business
from an average of 340
registrants per webcast
Contact: Camille Veyrier (veyrier@yole.fr),Marketing Communication Project Manager

CONTACT INFORMATION
o CONSULTINGANDSPECIFICANALYSIS,REPORT
BUSINESS
• North America:
• Steve LaFerriere, Senior Sales Director for Western US
Canada
Email: laferriere@yole.fr – + 1 310 600-8267
• Troy Blanchette, Senior Sales Director for Eastern US
Canada
Email: troy.blanchette@yole.fr – +1 704 859-0453
• Japan Rest ofAsia:
• Takashi Onozawa, General Manager,Asia Business
Development (Korea, Singapore, India ROA)
Email: onozawa@yole.fr - +81 34405-9204
• Miho Othake, Account Manager (Japan)
Email: ohtake@yole.fr - +81 3 4405 9204
• Itsuyo Oshiba, Account Manager (Japan)
Email: oshiba@yole.fr - +81-80-3577-3042
• Greater China: MavisWang, Director of Greater China Business
Development
Email: wang@yole.fr - +886 979 336 809
• Europe: Lizzie Levenez,EMEA Business Development Manager
Email: levenez@yole.fr - +49 15 123 544 182
• RoW: Jean-Christophe Eloy,CEO President,Yole Développement
Email eloy@yole.fr - +33 4 72 83 01 80
o FINANCIAL SERVICES (in partnershipwithWoodside
CapitalPartners)
• Jean-Christophe Eloy,CEO President
Email: eloy@yole.fr - +33 4 72 83 01 80
• Ivan Donaldson,VP of Financial Market Development
Email: ivan.donaldson@yole.fr - +1 208 850 3914
o GENERAL
• Public Relations: leroy@yole.fr - +33 4 72 83 01 89
• Email: info@yole.fr - +33 4 72 83 01 80
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