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About Image Segmentation Using Deep Learning: A Survey
This document surveys over 100 deep learning methods for image segmentation published until 2019. It groups the methods into 10 categories and provides a comprehensive review of popular network architectures, training strategies, performance on benchmarks, and challenges. Key contributions include analyzing aspects like datasets, architectures, loss functions, and future directions for the field. Popular CNN backbones for segmentation are reviewed, along with encoder-decoder models, multi-scale approaches, and generative adversarial models.
Detailed Information
| Author: | ['tilahun'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 23 |
| Language: | English |
| Format: | |
| Price: | FREE |
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