Overview🍩
This system is dedicated to the sustainable development of the ocean, combining underwater image colorization and restoration, object detection, and various neural network models to assist people in more effectively researching and understanding the ocean.
Paper📝
Yi Lin; Chung-Wei Hung; Yu-Jie Wang; Chih-Chia Liao; Yu-Shiuan Tsai, “Enhancing Underwater Images: Automatic Colorization using Deep Learning and Image Enhancement Techniques,” 2023 IEEE International Conference on Marine Artificial Intelligence and Law (ICMAIL) IEEE Xplore
Advantages
- Multimedia Support: Capable of loading images, videos, and web camera feeds.
- Scene Variety: Provides weights for underwater and land scenes.
- Ocean Sustainability Technology: Assists in the observation and research of the ocean.
Key Features
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Underwater Image Restoration: WaterNet, using weights trained on the provided dataset by the author.
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Automatic Colorization: neural-colorization, original weights provided by the author, and weights trained by us.
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Load Images, Videos, and Web Camera Feeds: Supports multimedia usage.
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Image Slider Comparison: Provides a more convenient and intuitive way to compare images.
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Object Recognition: YOLO v8, official original weights and weights trained for fish and colorblock recognition.
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Colorblock Capture and Analysis: Manually captures colorblocks to evaluate colorblock data in images.
