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WongKinYiu / yolov7

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
GNU General Public License v3.0
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Is it possible for YOLO team to replace nn.conv2d with nn.conv3d in the future for medical imaging #1426

Open frabob2017 opened 1 year ago

frabob2017 commented 1 year ago

Is it possible for YOLO team to replace nn.conv2d with nn.conv3d in the future because it is very useful for medical imaging which is 3d format? I believe if it change to 3d level, it would be robust in medical imaging. I try to understand your code and do it. But it is beyond my capability.

faizan1234567 commented 1 year ago

YOLOv7 doesn't support 3D convolution; however, you can use 3D segmentation models on medical imaging. i.e. UNET or Encoder-decoder architecture. They work with 3D medical imaging.

frabob2017 commented 1 year ago

YOLOv7 doesn't support 3D convolution; however, you can use 3D segmentation models on medical imaging. i.e. UNET or Encoder-decoder architecture. They work with 3D medical imaging.

Hello faizan, thank you for your answer. Yes, from the programing point view, I found that UNET is easy to implement 3D convolution. Although more difficult for programming, YOLO can do it. Hope YOLO can implement this feature also.