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About Deep Learning in Object Detection, PDF
This document summarizes recent advances in deep learning for object detection, segmentation, and recognition tasks in computer vision. It discusses how early neural networks were limited but have seen resurgence due to improved techniques like unsupervised pre-training and larger datasets. Deep learning now achieves state-of-the-art results for tasks like image classification, face detection, and pedestrian detection. The author's group has applied deep learning to problems like face parsing, pedestrian parsing, and face attribute recognition. Open questions remain around how to best formulate vision problems and make use of deep models' large learning capacity.
Detailed Information
| Author: | ['Raghavendra Shetty'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 64 |
| Language: | English |
| Format: | |
| Price: | FREE |
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