https://github.com/DaloroAT/first_break_picking
U-Net: Convolutional Networks for Biomedical Image Segmentation
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
U-Net: Convolutional Networks for Biomedical Image Segmentation
An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators
Detection and Segmentation of Custom Objects using High Distraction Photorealistic Synthetic Data
Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression
Bottom-up Object Detection by Grouping Extreme and Center Points
You Only Learn One Representation: Unified Network for Multiple Tasks
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
U-Net: Convolutional Networks for Biomedical Image Segmentation
Uncertainty-Aware Unsupervised Domain Adaptation in Object Detection
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
U-Net: Convolutional Networks for Biomedical Image Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.