ECEN 489 AI Spr 19 Lecture 23 CNN and Images.pdf - ECEN 489/ENGR 489 AI Technology and Applications Lecture 23 Convolutional Neural Networks Image

ECEN 489 AI Spr 19 Lecture 23 CNN and Images.pdf - ECEN...

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ECEN 489/ENGR 489 AI Technology and Applications Lecture 23: Convolutional Neural Networks & Image Learning 1
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Image Problems • Common Image Deep Learning Problems: –Image classification –Object detection –Segmentation • Practical issues in image analytics • Non-image applications of CNNs
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Image Classification • Place an image into a category, examples: –Handwritten digits (so last millennium since 1998, LeCun’s LeNet) –Dogs v Cats (please, make it stop!) –Medical Imaging is perhaps the best to look at: in 2012 more than 2B medical images were produced with about a 40% annual growth rate; in 2015, the largest medical image repository company had 30B images; Still plenty of challenges remain Src:IBM CLEF 2013 Src:Nowka 2015
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Image Classification Src:ImageCLEF 2011
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Image Classification • Modality Src:Cao, Chang, Smith CLEF 2013
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Image Classification • Modality Src:Pang, Du, Orgun, Yu, Medical & Biological Engineering & Computing, Jan 2019 Src:Lee, Zare, Muller, IET Image Processing, Nov 2018 Src: Ahn, Euijoon & Kim, Jinman & Kumar, Ashnil & Fulham, Michael & Feng, David Dagan Feng. (2018). Sparsity-based convolutional kernel network for unsupervised medical image analysis.
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ImageNet ILSVRC Challenge •1.2M images •1000 categories Olga Russakovsky*, Jia Deng*, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg and Li Fei-Fei. (* = equal contribution) ImageNet Large Scale Visual Recognition Challenge . International Journal of Computer Vision , 2015.
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ILSVRC image classification •Top-5 error: model makes 5 predictions, true label must be in top 5 •Top-1 error: only one prediction
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