seeing what matters Olivier DESPONT, ViDi Business Development Seoul, Vision Show, distributedby a member of
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1 seeing what matters distributedby Olivier DESPONT, ViDi Business Development Seoul, Vision Show, a member of
2 Excellence in industrial image analysis
3
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7 Enable computers, machines and robots to understand images such that they can meaningfully interact with the real world.
8 What is this? Where is Waldo? What is written? What is wrong?
9
10 Our Deep Learning approach 1 Collect 3 Train 2 Characterize 4 Validate
11 We converge to merge human capability with power, consistency and reliabilty of a machine
12 A revolutionisunderway Abundance of data Deep Learning Theory Affordable computing power And many more
13
14 Challenges in Industrial Applications 1 2 3
15 Brute Force vs Focus & Attention CNN
16 A unique architecture Core Focus Tool
17 Localization & identification Optical character reading Anomaly detection & segmentation Web inspection Scene tagging & classification Product identification Parts counting Discrete parts inspection Welding spot inspection Tracking Segmentation
18 1Collect images of objects 2Identify features on images 3Train model with ViDi blue 4Validate detection on untrained images NOV1014DDA 08:57 2 WY
19 ViDi blue Applications OCR (Optical Character Recognition) Steel Industry Tracking of steel sheets on cooling bed Steel Industry Parts Localization Cutting Tools Industry Fluid pressure control
20 Optical Character Recognition Recognition Rate > 98% (with error correction) images courtesy by SMS Concast AG, Zürich
21 OCR examples Stamped characters on metal ingots OCR-A on soft, semi-transparent plastic pouches Molded characters in plastic parts Inkjet printed text on bottom of aluminum cans Characters engraved in metal Pad-printed characters on gas tanks Characters placed closely to barcode OCR on non-flat surface with varying light conditions
22 Google Street View House Number Challenge
23 Cutting tools Parts localization in package
24 Cutting tools localization varying light conditions
25 Cutting tools localization occluded parts
26 Cutting tools localization occluded parts
27 1Collect images of good samples 3Validate model on images with defects 2Train images with ViDired unsupervised
28 ViDi red Applications Screw Inspection Medical Industry Chocolate meringue Inspection Food Inspection Fabric Inspection Textile Industry Cogwheel with decorated surface texture Watch Industry Web printing inspection Plastic Industry Metal Brushed Surface Inspection Watch Industry Texture Inspection Part Edges inspection Cutting tool Industry Pad printing Inspection Watch Industry
29 Textile Inspection I
30 1Collect images of good & bad samples 2Mark defects on bad images 3Train model with ViDi red supervised 4Validate model on untrained images supervised
31 ViDi red Applications supervised Cement Spot segmentation Bone detection Food Industry Green matter detection Food Industry Rail surface Inspection Steel Industry Cable connector Electronic Industry Cylinder Inspection Automotive Industry Dents and tears on capsules Pharmaceutical Industry
32 Cement Spot segmentation
33 1Collect images of products 2Tag images with their label 3Train model with ViDi green 4Validate model on untrained images
34 ViDi green Applications Wood Sorting Recycling Industry Products identification Food Industry / Logistic Handwritten OCR Bottle Sorting Recycling Industry
35 Bottle Sorting Brand vs? 98.4% correct classification
36 Chainable tools localization detection classification
37 Your Advantages
38 Key Advantages: Outperform Quality Inspectors Before Software Development effort 60quality inspectors Now 5Automatic Machines
39 Key Advantages: Speed up your time-to-market Classic Vision approach Before Software Development effort Now 60+days of development 0.5Days of development
40 The ViDi Challenge Key Advantages: Increase your solutions portfolio +100 Lost or refused applications provided by system integrators and machine builders 94% Now
41 I can do now in 3 days, what I did in 6-8 weeks Senior Vision Engineer Medical Industry Results are too good to be true; What is my mistake? Application Engineer System Integrator I finally found the Holy Grail! CEO Machine Manfuacturer
42 ViDi opens a new approach but not only for factory automation also for self-driving car also for surveillence also for tracking and also for medical diagnosis Are youreadyto joinus?
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