Convolutional Nets in Practice
Convolutional Nets in Practice
This lecture covers the concept of convolutional nets in practice and is a part of the Deep Learning Course at NYU's Center for Data Science.
Topics covered in this lesson
Chapters:
00:00:00 – Welcome to class
00:00:09 – ConvNets in practice
00:01:49 – What are convolutions good for?
00:08:39 – Why do we need to stack layers?
00:13:50 – Object detection, multiple object recognition
00:17:25 – Multiple character recognition
00:19:31 – Sliding window ConvNet
00:23:20 – Face detection
00:25:55 – Whiteboard time!
00:31:30 – Q&A
00:33:40 – Semantic segmentation
00:38:54 – Robot navigation using semantic segmentation
00:43:42 – Category-level semantic segmentation
00:46:43 – FPGA ConvNet accelerator
00:47:56 – Error rate on ImageNet
00:49:23 – ResNet
00:50:36 – Networks comparison
External Links
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