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underwater-imaging

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Addalin / Unerwater_Mitsuba_Rendering

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A framework for physics-based rendering of underwater images using Mitsuba 0.6 This work is part of simulation work done in[1]. [1] Adi Vainiger, Yoav Y. Schechner, Tali Treibitz, Aviad Avni, and David S. Timor, "Optical wide-field tomography of sediment resuspension," Opt. Express 27, A766-A778 (2019) https://opg.optica.org/oe/abstract.cfm?uri=o

tomography physics-based-simulation mitsuba-renderer underwater-imaging
  • Updated Dec 5, 2022
  • Python

tinh2044 / YOLO12-UnderWater

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YOLOv12 Underwater Object Detection is an open-source suite for underwater object detection, built on YOLOv12. It offers an end-to-end pipeline with GPU-accelerated training, customizable data augmentations, real-time inference via Gradio, and support for model export (ONNX & PyTorch).

computer-vision deep-learning image-processing pytorch gpu-acceleration object-detection gradio evaluation-metrics data-augmentation attention-mechanisms onnx model-export training-pipeline mixed-precision-training underwater-object-detection underwater-imaging real-time-inference yolov12 environmental-adaptation brackish-water
  • Updated Apr 28, 2025
  • Python

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