Retrieval of Diverse Images by Pre-filtering and Hierarchical Clustering

•

0 recomendaciones•170 vistas

In this paper, we describe our approach and its results for MediaEval 2014 Retrieving Diverse Social Images Task. The basic idea of our proposed method is to filter out non-relevant images at the beginning of the process and then construct a hierarchical tree which allows to cluster the images with different criteria on visual and textual features. Experimental results shown that it is stable and has little fluctuation with the number of topics. http://ceur-ws.org/Vol-1263/mediaeval2014_submission_4.pdf

Software

•
•
Input
Step 1. Pre-filtering
Step 2. Hierarchical Clustering
Step 3. Tree Refining
Step 4. Result Reranking
Output

Recomendados

Recod @ MediaEval 2014: Diverse Social Images Retrievalmultimediaeval

CUNI at MediaEval 2014 Search and Hyperlinking Task: Search Task Experimentsmultimediaeval

Nni v7multimediaeval

CUNI at MediaEval 2014 Search and Hyperlinking Task: Visual and Prosodic Feat...multimediaeval

A Unified Framework for Retrieving Diverse Social Imagesmultimediaeval

The NNI Query-by-Example System for MediaEval 2014multimediaeval

TUKE System for MediaEval 2014 QUESSTmultimediaeval

Classification of Strokes in Table Tennis with a Three Stream Spatio-Temporal...multimediaeval

HCMUS at MediaEval 2020: Ensembles of Temporal Deep Neural Networks for Table...multimediaeval

Sports Video Classification: Classification of Strokes in Table Tennis for Me...multimediaeval

Predicting Media Memorability from a Multimodal Late Fusion of Self-Attention...multimediaeval

Essex-NLIP at MediaEval Predicting Media Memorability 2020 Taskmultimediaeval

Overview of MediaEval 2020 Predicting Media Memorability task: What Makes a V...multimediaeval

Fooling an Automatic Image Quality Estimatormultimediaeval

Fooling Blind Image Quality Assessment by Optimizing a Human-Understandable C...multimediaeval

Pixel Privacy: Quality Camouflage for Social Imagesmultimediaeval

HCMUS at MediaEval 2020:Image-Text Fusion for Automatic News-Images Re-Matchingmultimediaeval

Efficient Supervision Net: Polyp Segmentation using EfficientNet and Attentio...multimediaeval

HCMUS at Medico Automatic Polyp Segmentation Task 2020: PraNet and ResUnet++ ...multimediaeval

Depth-wise Separable Atrous Convolution for Polyps Segmentation in Gastro-Int...multimediaeval

Deep Conditional Adversarial learning for polyp Segmentationmultimediaeval

A Temporal-Spatial Attention Model for Medical Image Detectionmultimediaeval

HCMUS-Juniors 2020 at Medico Task in MediaEval 2020: Refined Deep Neural Netw...multimediaeval

Fine-tuning for Polyp Segmentation with Attentionmultimediaeval

Bigger Networks are not Always Better: Deep Convolutional Neural Networks for...multimediaeval

Insights for wellbeing: Predicting Personal Air Quality Index using Regressio...multimediaeval

Use Visual Features From Surrounding Scenes to Improve Personal Air Quality ...multimediaeval

Personal Air Quality Index Prediction Using Inverse Distance Weighting Methodmultimediaeval

Unit 1.1 Excite Part 1, class 9, cbse...aditisharan08

Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...MyIntelliSource, Inc.

Más contenido relacionado

Más de multimediaeval