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About Counting in Dense Crowds Using Deep Learning
This document proposes a method for counting people in dense crowd images using deep learning. The method fine-tunes a pre-trained convolutional neural network on image patches extracted from crowd images. Various loss functions are tested for training, including a novel difference-to-sum ratio loss function. The method can accurately estimate crowd sizes ranging from 100 to 4500 people, outperforming previous methods that work best for smaller crowds of 10-60 people.
Detailed Information
| Author: | ['Joseph Jeremy'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 6 |
| Language: | English |
| Format: | |
| Price: | FREE |
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