Artificial intelligence (AI) has been applied to various methods for digital image creation and editing in Adobe Photoshop 2022. “Inartful” common art and digital photos can be re-imagined using such “neural filters” as style transfer, landscape mixer, color transfer, harmonization, Depth Blur, colorization, and others. The filters can be additive or reductive, or both (of various elements). This session offers walk-throughs of these various Neural Filter features in Adobe Photoshop 2022 (using AI Adobe Sensei). Come explore the “imagination” in a digital image editing software.

1. CO-CREATING COMMON ART
WITH AI TOOLS
IN ADOBE PHOTOSHOP 2022:
STYLE TRANSFER, LANDSCAPE MIXER, COLOR TRANSFER, HARMONIZATION, DEPTH BLUR, AND COLORIZATION
SHALIN HAI-JEW
SIDLIT 2022
JULY 27 – 29, 2022

2. PRESENTATION OVERVIEW
• ARTIFICIAL INTELLIGENCE (AI) HAS BEEN APPLIED TO VARIOUS METHODS FOR DIGITAL IMAGE
CREATION AND EDITING IN ADOBE PHOTOSHOP 2022. “INARTFUL” COMMON ART AND
DIGITAL PHOTOS CAN BE RE-IMAGINED USING SUCH “NEURAL FILTERS” AS STYLE TRANSFER,
LANDSCAPE MIXER, COLOR TRANSFER, HARMONIZATION, DEPTH BLUR, COLORIZATION, AND
OTHERS. THE FILTERS CAN BE ADDITIVE OR REDUCTIVE, OR BOTH (OF VARIOUS ELEMENTS).
THIS SESSION OFFERS WALK-THROUGHS OF THESE VARIOUS NEURAL FILTER FEATURES IN
ADOBE PHOTOSHOP 2022 (USING AI ADOBE SENSEI). COME EXPLORE THE “IMAGINATION” IN
A DIGITAL IMAGE EDITING SOFTWARE.
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3. ABOUT “COMMON ART”
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4. “COMMON ART”
• “COMMON ART” IS ART CREATED BY COMMON FOLK, A NON-PROFESSIONAL, AN AMATEUR,
OFTEN WITH LITTLE TO NO FORMAL TRAINING IN THE CREATING OF ART. COMMON ART IS A
PRACTICE FROM ANTIQUITY THROUGH THE PRESENT. THE MAKING OF COMMON ART IS FOR
PERSONAL EXPRESSION, CRAFTING, STRESS RELIEF, AND ENJOYMENT, AMONG OTHERS.
• “ART” IS USED IN A VERY GENERAL SENSE HERE.
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5. ARTIFICIAL NEURAL NETWORKS (ANNS)
(PER THE “NEURAL” FILTER REFERENCES)
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6. ANNS
AN ARTIFICIAL NEURAL NETWORK WITH
HIDDEN LAYERS
CAN HAVE MULTIPLE INPUT AND OUTPUT
NODES (ALBEIT NOT DIRECTLY DEPICTED HERE)
ARTIFICIAL NEURONS THAT PROCESS INPUTS
AND OUTPUTS THROUGH VARIOUS LAYERS TO
PARTICULAR DESIGNED OUTPUTS
CREATED USING AI
SOME MYSTERY IN THE HIDDEN LAYERS IN
TERMS OF EXACT PROCESSING
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7. SOME NEURAL FILTERS
IN ADOBE PHOTOSHOP 2022
(AND THERE ARE MORE IN THE PIPELINE!)
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8. 8

9. NEURAL FILTERS
• INTERACTS WITH THE SEEDING IMAGE (INPUT)
• SEEDING IMAGE GOES THROUGH VARIOUS PROCESSES
• OUTPUT IS A NEW IMAGE, WHICH HAS NEVER EXISTED BEFORE
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10. STYLE TRANSFER
BY ARTIST STYLES BY IMAGE STYLES
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11. EXPLORING THE SOURCE IMAGES
FOR THE STYLE TRANSFERS
• STYLE TRANSFERS ARE SEEDED WITH WORKS FROM THE 19TH, 20TH, AND 21ST CENTURY, FROM
MOSTLY WESTERN BUT SOME EASTERN TRADITIONS.
• SOME OF THE RECOGNIZABLE WORKS SEEM TO BE IN THE PUBLIC DOMAIN.
• ANYWAY, WHAT IS EXTRACTED FROM THEM IS AN ANN. STILL, THE LAW ON WHETHER SUCH
EXTRACTIONS IS SETTLED IS UNCLEAR.
• A NUMBER OF THE OTHER WORKS ARE MORE MODERNIST AND PERHAPS SOMEWHAT
DERIVATIVE OF STOCK IMAGES AND PHOTOS AND WERE NOT EASILY IDENTIFIABLE. THESE DID
HAVE COLOR PALETTES AND TRANSFERRABLE ELEMENTS FOR THE NEURAL FILTERS, THOUGH.
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12. EXPLORING THE SOURCE IMAGES
FOR THE STYLE TRANSFERS (CONT.)
• THE VISUALS WERE BACKTRACKED FROM IN-TOOL THUMBNAILS THROUGH A REVERSE SEARCH
ENGINE (TINEYE) TO A WORK…AND THE DATA WAS VERIFIED THROUGH ADDITIONAL FOLLOW-ON
SEARCHES. FOR SOME, A SEARCH OF SOME 54 BILLION IMAGES ON TINEYE DID NOT RESULT IN
ANY FINDINGS.
• THOSE OUTSIDE OF COPYRIGHT PROTECTIONS HAVE VERSIONS THAT HAVE BEEN CREATED.
• FINDING NAMES AND TITLES AND DATES WERE NOT ALWAYS STRAIGHTFORWARD, GIVEN DERIVATIONS,
GIVEN DILUTION OF THE ORIGINAL WORKS. SOME RELATED TEXT WERE GENERIC TEXTUAL DESCRIPTORS.
• SOME WHO ARE VERSED IN ART HISTORY WOULD APPRECIATE THE TIE-INS AND ADDITIONAL
ARTFUL EVOCATIONS. IN ANOTHER SENSE, THE CO-CREATED WORKS ARE UNMOORED FROM BOTH
ORIGINATING “PARENTS.”
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13. 13

14. ARTIST STYLE: STYLE TRANSFERS
• FOR ARTIST STYLE, SOME OF THE SEEDING WORKS INCLUDE THE FOLLOWING:
• VINCENT VAN GOGH’S “SELF-PORTRAIT (1889); “WHEAT FIELD WITH CYPRESSES” (1889)
• KATSUSHIKA HOKUSAI’S “RAINSTORM BENEATH THE SUMMIT” (1820 – 1823)
• PAUL GAUGUIN’S “HAIL MARY” (1891), FROM THE TAHITIAN WOMEN SERIES; “THE LEMON PICKER” (1891)
• EDVARD MUNCH’S “THE ANXIETY” (1894)
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15. ARTIST STYLE: STYLE TRANSFERS (CONT.)
• PAUL CEZANNE’S “HOUSES ALONG A ROAD” (1881)
• BERTHE MORISOT’S “WOMAN PICKING FLOWERS” (1879)
• GEORGES SEURAT’S “CADET FROM SAINT CYR” (1884)
• CLAUDE MONET’S “WATER LILIES” (1917)
• MAYNARD DIXON’S “WILD HORSES OF NEVADA” (1927)
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16. 16

17. IMAGE STYLE: STYLE TRANSFERS
• FOR IMAGE STYLE, SOME OF THE SEEDING WORKS INCLUDE THE FOLLOWING:
• KATSUSHIKA HOKUSAI’S “UNDER THE WAVE OFF KANAGAWA” / “THE GREAT WAVE” (1831)
• FRANCIS PICABIA’S “EDTAONIST” (OR “ECCLESIASTIC”) (1913); “UDNIE” (1913)
• VINCENT VAN GOGH’S “SELF-PORTRAIT WITH A STRAW HAT” (1887); “THE NIGHT CAFÉ” (1888);
“STARRY NIGHT” (1889); “OLIVE TREES” (1889); “HOUSE AND FIGURE” (1890)
• EDVARD MUNCH’S “THE SCREAM” (1893)
• PAUL GAUGUIN’S “THREE TAHITIAN WOMEN” (1896)
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18. IMAGE STYLE: STYLE TRANSFERS (CONT.)
• MANY WORKS WERE NOT MATCHED TO ANYTHING ONLINE. SOME BROUGHT UP STOCK IMAGES.
SOME BROUGHT UP PHOTOS. (SOME OF THE WORKS MAY BE RECOLORED OR ARTFUL OVERLAYS
ON EXISTING PHOTOS.)
• THERE WAS A DICHOTOMY BETWEEN THE OLDER FORMALIST ARTWORKS AND THE MORE MODERNIST-
DIGITAL “FILLER” WORKS.
• TWO OF MY ABSOLUTE FAVORITE NEURAL FILTERS WERE FILTERS…THAT I COULD NOT IDENTIFY TO AN
ARTIST NAME OR TITLE OR DATE. I LIKE ONE OF THE ORIGINAL WORKS BUT MAYBE NOT THE OTHER AS
MUCH. IT’S JUST THE ABSTRACTION FROM THAT LATTER WORK THAT WORKS WELL FOR ME. (SO MUCH
OF THIS IS SUBJECTIVE.)
• I DID TRY TO FIND DOCUMENTATION ON THE VARIOUS WORKS, BUT I CAME UP SHORT.
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19. ABOUT STYLE TRANSFERS FROM
INDIVIDUAL ART WORKS
• IT HELPS TO THINK OF EACH ARTWORK USED IN THE ARTIFICIAL NEURAL NETWORK (ANN) FOR
STYLE AS A FEATURE SET OF LINES, COLORS, TEXTURES, AND SO ON. THIS FEATURE SET MAY BE
PERCEIVED AS A KIND OF VISUAL GIST.
• IT HELPS TO THINK OF THE WORKS AS BEING ABSTRACTED OUT INTO SEPARATE APPLIED STYLES.
• YOU’RE NOT LOOKING AT THE ARTWORK IN FRONT OF YOU, BUT YOU’RE LOOKING AT ITS FEATURES.
• IT HELPS TO THINK OF MYSTERY, WITH THE ANN’S HIDDEN LAYERS SELECTING VISUAL FEATURES
AND CREATING RULES FOR WHEN TO APPLY THOSE FEATURES TO THE SEEDING WORK (AND BASED
ON THE PARAMETER SETTINGS).
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20. FORMALIST SCHOOLS OF ART STYLES
• MANY WORKS SEEM TO BE OF THE IMPRESSIONIST SCHOOL.
• MORE MODERN WORKS SEEM TO BE OF THE REALIST SCHOOL, GENERALLY SPEAKING. THERE
IS ALSO SOME DADA.
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21. STYLE TRANSFER - CUSTOM
• CAN “STYLE TRANSFER” FROM AN ORIGINAL OR
“CUSTOM” IMAGE
• THE ELEMENTS OF STYLE INCLUDE ASPECTS OF THE
ORIGINAL SOURCE IMAGE (THAT INFORMS THE STYLE):
COLOR, LINE, TEXTURE (LESS COMPOSITION)
• WORKS LIKE A MELD WHERE THE SEEDING IMAGE ALSO
INFORMS THE NEW VISUAL
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22. LANDSCAPE MIXER
THIS NEURAL FILTER ENABLES THE DRAWING OF
VARIOUS LANDSCAPE SCENES (LANDFORMS),
OFTEN WITH DIFFERENT SEASONS AND TIMES
OF DAY (IN TERMS OF LIGHTING).
THIS FILTER DEMONSTRATES THE POWERFUL
NUANCES AVAILABLE WITH ANN PROCESSING.
THE VARIOUS NEURAL FILTERS IN THE
LANDSCAPE MIXER SET VARY IN TERMS OF THE
ACTUAL “CREATION” OF THE ILLUSION OF
VARIOUS LANDFORMS.
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23. COLOR TRANSFER
THE COLOR TRANSFER NEURAL FILTER RECOLORS THE EXISTING
COLORS IN A SEEDING IMAGE.
THE MORE VARIANCE IN ORIGINAL COLORS, THE MORE MULTI-
COLOR COLOR TRANSFER NEURAL FILTERS CAN APPLY.
THERE ARE SOME MONOCHROMATIC OR BI- OR TRI-CHROMATIC
COLOR TRANSFER NEURAL FILTERS. (SOME “COLOR” TRANSFERS
CAN INVOLVE THE REMOVAL OF COLORS AND GOING TO DARKS
AND LIGHTS, VARYING VALUES.)
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24. HARMONIZATION
THE HARMONIZATION NEURAL FILTER
ALIGNS THE COLORS ACROSS MULTIPLE
COMBINED LAYERS FOR MORE ALIGNED
COLORS (AT A MORE NUANCED LEVEL).
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25. DEPTH BLUR
ENABLES THE DEFINING OF THE FOCAL
DISTANCE
ENABLES CLICKING ON A PART OF AN
IMAGE FOR OBJECT FOCUS (AND
EVERYTHING “BEHIND” CAN BE BLURRED
AND / OR HAZED VISUALLY)
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26. COLORIZATION
THE COLORIZATION NEURAL FILTER INVOLVES
THE AI ADDING OF COLOR TO A GRAYSCALE
(MIDTONES) VISUAL.
THE COLORS ADDED ARE NOT MERELY
COMMUNICATING POTENTIAL COLORS IN A
REAL-WORLD CONTEXT…BUT APPARENTLY ADD
SOMETHING OF DRAMA TO THE COLORING
TO CATCH THE EYES. [A COLOR IMAGE THAT IS
GRAYSCALED AND THEN HAS “COLORIZATION”
APPLIED DOES NOT RETURN TO ITS ORIGINAL
COLOR STATE…WHICH IS TECHNICALLY
UNKNOWABLE FROM THE GRAY. RATHER, THE
NEW COLORIZED IMAGE IS A NEW VERSION.]
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27. COLORIZATION PROFILES
• RETRO HIGH CONTRAST
• RETRO BLUE BROWN
• RETRO LIGHT YELLOW
• RETRO PURPLE YELLOW
• RETRO BRIGHT
• RETRO RED
• RETRO GREEN
• RETRO FADED
• RETRO DENIM
• RETRO DARK
• RETRO BROWN
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28. ELUSIVE VISUAL NUANCES
• THERE ARE ELUSIVE VISUAL NUANCES TO VARIOUS STYLES
AND NEURAL FILTERS.
• PERHAPS THERE IS SOMETHING EVOKED OF MOOD.
• PERHAPS THERE ARE ASPECTS OF A WORK THAT CONVEY
“RETRO.”
• PERHAPS VARIOUS ASPECTS OF THE STYLE ARE
HIGHLIGHTED OR EMPHASIZED OR DISAPPEARED BASED
ON THE PARAMETER SETTINGS…AND BASED ON THE
UNDERLYING SEEDING IMAGE.
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29. NEURAL FILTERS FOR CO-CREATED ART
HUMAN
• THE HUMAN DECIDES WHAT IMAGES TO USE AS SEEDING
VISUALS. THESE CAN BE BORN-ANALOG OR BORN-
DIGITAL…OR SOME COMBINATION.
• THE PROCESS IS SEQUENCE-SENSITIVE.
• THERE CAN BE PRE-PROCESSING; THERE CAN BE POST-
PROCESSING.
• HEIGHTEN THE SPATIAL RESOLUTION BEFORE THE NEURAL
FILTERING.
• INTEGRATE VARIOUS LAYERS FOR DIFFERENT VISUAL EFFECTS.
• ENGAGE LIGHT COMPOSITING.
COMPUTER
• THE NEURAL FILTERS ARE SOMEWHAT
PREDICTABLE AFTER SOME EXPERIENCES
WITH EACH ONE AND AFTER SOME
SAMPLING.
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30. NEURAL FILTERS FOR CO-CREATED ART
A MEETING OF PEOPLE WITH MACHINES
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31. NEURAL FILTERS FOR CO-CREATED ART (CONT.)
HUMAN
• THE HUMAN DECIDES (A LITTLE INDIRECTLY)
WHAT FEATURES TO SHOWCASE IN THE
NEURAL FILTERED IMAGE.
COMPUTER
• THE COMPUTER OFFERS PREVIEWS OF THE
VARIOUS APPLIED FILTERS.
• THE SYSTEM DOES NOT FORCE A “COMMIT.” IT
OFFERS THE OVERLAY TENTATIVELY AND FAIRLY
ACCURATELY.
• IT HELPS IF THE PERSON CAN ENGAGE VISUAL
THINKING AND ANTICIPATING LOOKS-AND-
FEELS. MUCH OF THIS IS MECHANISTIC.
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32. NEURAL FILTERS FOR CO-CREATED ART (CONT.)
HUMAN
• THERE IS THE SELECTION OF THE NEURAL FILTER
(OR FILTERS IN SEQUENCE).
• THERE ARE THE SLIDER / ADJUSTMENTS TO THE
NEURAL FILTER(S).
• THERE IS THE SELECTION OF DIGITAL IMAGE
EDITS OUTSIDE OF THE NEURAL FILTERS.
• THE FILTER GALLERY ENABLES A WIDE RANGE
OF OTHER VISUAL EFFECTS.
COMPUTER
• THE SOFTWARE PROGRAM ENABLES A WIDE
RANGE OF OTHER EDITS AND EFFECTS.
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33. NEURAL FILTERS FOR CO-CREATED ART (CONT.)
HUMAN
• THERE IS THE USE OF LAYERS AND MASKING
AND TRANSPARENCIES FOR DIFFERENT VISUAL
EFFECTS.
• THE HUMAN DECIDES WHAT IS AESTHETICALLY
PLEASING.
• IT IS OKAY TO HAVE “UGLY” LIMINAL STAGES
AS LONG AS THE FINAL VISUAL WORKS.
COMPUTER
• THE SOFTWARE CREATES A SENSE OF
VISUAL COHESION WITH THE NEURAL
FILTERS.
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34. NEURAL FILTERS FOR CO-CREATED ART (CONT.)
HUMAN
• THE HUMAN CAN NARRATE A STORY
AROUND A CO-CREATED VISUAL ART.
• THE STORY MAY BE EXPERIENTIAL.
• ALL VISUAL ARTWORKS HAVE ASPECTS THAT
CANNOT BE VERBALLY OR TEXTUALLY
DESCRIBED. THERE IS A LEVEL OF
“INCHOATE” IN THE ARTWORKS.
COMPUTER
• THE COMPUTER CAN CREATE A NUMBER OF
VARIATIONS FROM ONE SEED.
• IT IS WHOLLY POSSIBLE TO FORGET THE
SEQUENCED STEPS TO CREATE A VISUAL.
• IT HELPS TO SAVE AN EDITABLE VERSION OF
THE FILE INSTEAD OF JUST THE FIXED DIGITAL
IMAGE AT THE END, IF THERE ARE OTHER
NEURAL FILTERS AND EDITS THAT ARE TO BE
TRIED.
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35. WHAT THE SEEDING IMAGE BRINGS?
• THE SEEDING IMAGE, DEPENDING ON THE NEURAL FILTER, CAN BRING ANY OR ALL OF THE
FOLLOWING TO THE COLLABORATION:
• COMPOSITION
• LINES
• COLORS
• TEXTURES
• BRIGHTNESS / DARKNESS
• AND OTHER COMBINATIONS
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36. WHAT THE SEEDING IMAGE BRINGS? (CONT.)
• WHATEVER THE SEEDING IMAGE BRINGS, THE NEURAL FILTERS WILL COVER OVER OR MUTE
SOME ASPECTS; THEY WILL HIGHLIGHT OR EMPHASIZE OTHER ASPECTS.
• THE NEURAL FILTERS DO NOT COLOR OVER ALPHA CHANNELS. THEY COLOR OVER
TRANSPARENCY GRADIENTS POORLY OR VERY LIGHTLY.
• NEURAL FILTERS TEND TO DO BETTER WITH COLORS.
• COLOR HALFTONES MAINTAIN THAT SPOTTED PATTERN.
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37. PRE- AND POST-PROCESSING
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38. DIGITAL IMAGE PREPARATION AND POST-NEURAL
FILTER PREPARATION
PRE-PROCESSING
• SAVE RAW PHOTOS AS COMMON DIGITAL
IMAGE FORMAT TYPES.
• JUMP THE RESOLUTION ON THE VISUALS.
• CONDUCT DIGITAL IMAGE EDITS (CONTRAST,
LINES, OTHERS) FOR PARTICULAR ANTICIPATED
NEURAL NETWORK EFFECTS.
• ENGAGE LIGHT COMPOSITING.
POST-PROCESSING
• SAVE OUT THE NEURAL-FILTERED IMAGE.
• MAKE ANY ADDITIONAL DIGITAL IMAGE
EDITS.
• SLICE. FLIP. CRUMPLE. FOLD. COLOR.
DRAW OVER. DRAW UNDER.
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39. WHAT APPEALS TO ME VISUALLY?
• FOR THE LONGEST TIME, I HAVE LIKE “STRANGE” VISUAL EFFECTS. I LIKE STRANGE SURPRISES.
• OVER TIME, I HAVE LEARNED TO LIKE USING SLIDERS AND MORE NUANCED APPROACHES.
• IT HELPS TO VERSION ALONG THE WAY, SO THAT THERE ARE INTERMEDIATE VISUALS THAT MAY
BE USED ALONG DIFFERENT BRANCHES AND PATHS.
• IT HELPS TO CONSUME OTHERS’ WORKS, SO THAT ONE CAN LEARN FROM HOW OTHERS
PROCEED.
• YOU DON’T WANT TO GO SO FAST THAT YOU LOSE THE LEARNING ALONG THE WAY.
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40. GALLERY
UNEDITED
SEEDING ALCOHOL INK PAINTINGS
SEEDING DIGITAL PHOTOGRAPHS
MORE POWERFUL
OVERLAYS
STYLE TRANSFER
LANDSCAPE MIXER
COLOR TRANSFER
MORE SUBTLE OVERLAYS
HARMONIZATION
DEPTH BLUR
COLORIZATION
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41. SEEDING ALCOHOL INK PAINTINGS
(A SELECTION)
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42. 42

43. 43

44. 44

45. 45

46. 46

47. 47

48. 48

49. SEEDING DIGITAL PHOTOGRAPHS
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50. 50

51. 51

52. 52

53. 53

54. 54

55. 55

56. 56

57. 57

58. STYLE TRANSFER
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59. 59

60. 60

61. 61

62. 62

63. 63

64. 64

65. 65

66. 66

67. 67

68. 68

69. 69

70. 70

71. 71

72. 72

73. 73

74. 74

75. 75

76. LANDSCAPE MIXER
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77. 77

78. 78

79. 79

80. 80

81. 81

82. 82

83. 83

84. 84

85. 85

86. 86

87. COLOR TRANSFER
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88. 88

89. 89

90. 90

91. 91

92. 92

93. 93

94. 94

95. 95

96. 96

97. HARMONIZATION
FOR MULTI-LAYER IMAGES
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98. 98

99. DEPTH BLUR
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100. 100

101. 101

102. COLORIZATION
FROM B/W, FROM GRAYSCALE SEEDING VISUALS
CAN WORK WITH COLOR IMAGES, TOO, BUT THESE WORK BETTER IF THE COLORS ARE MUTED
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103. 103

104. 104

105. 105

106. 106

107. 107

108. 108

109. 109

110. 110

111. IN THE CO-CREATION, IS THIS MORE HUMAN
OR MORE MACHINE?
WHAT DO YOU THINK? WHY?
WHAT DO YOU THINK THE LEGAL ESTABLISHMENT HAS SAID SO FAR ABOUT ART CREATED BY AI
ALONE?
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112. CO-CREATED ART IS CYBORGIAN
• THIS CO-CREATED ART IS
• PART-HUMAN, PART-MACHINE;
• HUMAN INTELLECT-BASED, MACHINE INTELLECT-BASED;
• AND BORN-ANALOG IN SOME CASES.
• AND BORN-DIGITAL IN OTHERS.
• OR THE CO-CREATED ART IS ALL HUMAN WITH THE SUPPORT OF AI-BASED TOOLS.
• IS THE ASSERTION OF “CO-CREATION” WITH AN AI ROMANTICIZING THE ACTS OF CREATION? THE
HARNESSING OF A TECHNICAL TOOL?
• OR IS IT GIVING THE HUMAN TOO MUCH CREDIT, GIVEN THE HEAVY (BUT FAST) COMPUTATION IN AI
APPLICATIONS?
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113. GENERAL ADVICE
• EXPERIMENT BROADLY. TRY EVERYTHING. PAY ATTENTION AS YOU’RE EXPERIMENTING.
HARNESS SERENDIPITY.
• BE SURE TO PRESERVE A COPY OF EVERY LOOK THAT YOU LIKE. SOMETIMES, IT’S VERY HARD TO
RECAPTURE A PARTICULAR LOOK.
• DON’T FORGET THE OTHER DIGITAL IMAGE EDITING TOOLS (AND EQUIPMENT: DIGITAL
CAMERAS, SCANNERS, PEN-AND-TABLET SETUPS) (AND ANALOG MATERIALS) AND SUCH, JUST
BECAUSE NEURAL FILTERS ARE SO DAZZLING THAT THEY CAN OVERSHADOW THE OTHER
ELEMENTS AND TOOLS.
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114. CONTACT
• DR. SHALIN HAI-JEW
• ITS, KANSAS STATE UNIVERSITY
• SHALIN@KSU.EDU
• 785-532-5262
• A CLARIFICATION: A FEW OF THE WORKS HAD MULTIPLE DIGITAL EDITS APPLIED INSTEAD OF JUST ONE
NEURAL FILTER. HOWEVER, THE MAIN NEURAL FILTER APPLIED WAS USED TO DECIDE WHICH CATEGORY THE
VISUAL WAS PLACED IN. I ALSO USED A FEW SEEDING LINE ART WORKS FOR DIFFERENT VISUAL EFFECTS.
• MISTAKES: I DID DUE DILIGENCE TO TRY TO PRESENT THIS AS ACCURATELY AS POSSIBLE GIVEN THE AVAILABLE
DOCUMENTATION AND FIRST-HAND EXPERIENCES. ALL MISTAKES ARE MY OWN. PLEASE FEEL FREE TO EMAIL IF
YOU HAVE FOUND A MISTAKE.
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