14. Issues with NN
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Machine Vision - Introduction 14
• Take an exceedingly long time to train
• Open architectures resulting in relatively simpler execution
• Low barrier for entry
• Transfer Learning
17. System of CNN
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Machine Vision - Introduction 17
• Supervised
• Large and Complex
• Object Detection
• SSD - Single Shot MultiBox Detector
• Self Driving Cars
• Style Transfer
• Transfer Learning
18. Prerequisite
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Machine Vision - Introduction 18
• You are familiar with python
• Scikit learn
• Standard Machine Learning Algorithms
19. Theme for the Labs
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Machine Vision - Introduction 19
• CNN based Systems
• Exercise (Just for yourself, no need to code)
• Train breast Cancer dataset using PyTorch
• Train breast Cancer dataset using Tenserflow Keras
• Use Google Cloud Credits posted in the announcement.
• I have requested more through AWS. Will update you on
that when I hear back.
20. Theme for the Labs
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Machine Vision - Introduction 20
• 10 labs 20 points each
• Weekly submissions due on Thursday, with 48 hours grace
period
• Graded over correctness and attention+explainations of
details
21. Theme for the Quizzes
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Machine Vision - Introduction 21
• 10/11 quizzes 10 points each
• Five Questions on weekly readings
• Opens on Monday and stays open for a week.
22. Theme for Project
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Machine Vision - Introduction 22
• Prepare for submission to the IEEE Winter Conference on
Applications of Computer Vision (WACV)
• 4 steps
• Follow WACV guidelines
• Submission is not mandatory but is highly advised.