Transfer Learning Applied to Computer Vision Problems: Survey on Current Progress, Limitations, and Opportunities
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866910601549185024 |
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| author | Panda, Aaryan Panigrahi, Damodar Mitra, Shaswata Mittal, Sudip Rahimi, Shahram |
| author_facet | Panda, Aaryan Panigrahi, Damodar Mitra, Shaswata Mittal, Sudip Rahimi, Shahram |
| contents | The field of Computer Vision (CV) has faced challenges. Initially, it relied on handcrafted features and rule-based algorithms, resulting in limited accuracy. The introduction of machine learning (ML) has brought progress, particularly Transfer Learning (TL), which addresses various CV problems by reusing pre-trained models. TL requires less data and computing while delivering nearly equal accuracy, making it a prominent technique in the CV landscape. Our research focuses on TL development and how CV applications use it to solve real-world problems. We discuss recent developments, limitations, and opportunities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_07736 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Transfer Learning Applied to Computer Vision Problems: Survey on Current Progress, Limitations, and Opportunities Panda, Aaryan Panigrahi, Damodar Mitra, Shaswata Mittal, Sudip Rahimi, Shahram Computer Vision and Pattern Recognition Artificial Intelligence The field of Computer Vision (CV) has faced challenges. Initially, it relied on handcrafted features and rule-based algorithms, resulting in limited accuracy. The introduction of machine learning (ML) has brought progress, particularly Transfer Learning (TL), which addresses various CV problems by reusing pre-trained models. TL requires less data and computing while delivering nearly equal accuracy, making it a prominent technique in the CV landscape. Our research focuses on TL development and how CV applications use it to solve real-world problems. We discuss recent developments, limitations, and opportunities. |
| title | Transfer Learning Applied to Computer Vision Problems: Survey on Current Progress, Limitations, and Opportunities |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence |
| url | https://arxiv.org/abs/2409.07736 |