https://github.com/2023-MindSpore-1/ms-code-17/tree/main/CLIFF
CLIFF: Contrastive Learning for Improving Faithfulness and Factuality in Abstractive Summarization
Papers with Code 아카이브
2D Classification
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/2023-MindSpore-1/ms-code-170
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-174
https://github.com/2023-MindSpore-1/ms-code-175
https://github.com/2023-MindSpore-1/ms-code-176
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
https://github.com/2023-MindSpore-1/ms-code-177
https://github.com/2023-MindSpore-1/ms-code-179
Bridged Transformer for Vision and Point Cloud 3D Object Detection
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/ISyNet
ISyNet: Convolutional Neural Networks design for AI accelerator
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/lite-hrnet
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/lresnet100e_ir
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/m2det
M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network
https://github.com/2023-MindSpore-1/ms-code-181
Side-Aware Boundary Localization for More Precise Object Detection
https://github.com/2023-MindSpore-1/ms-code-182
https://github.com/2023-MindSpore-1/ms-code-183
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-184
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/2023-MindSpore-1/ms-code-185
https://github.com/2023-MindSpore-1/ms-code-186
https://github.com/2023-MindSpore-1/ms-code-189/tree/main/modelarts
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/2023-MindSpore-1/ms-code-19
https://github.com/2023-MindSpore-1/ms-code-191
https://github.com/2023-MindSpore-1/ms-code-194
https://github.com/2023-MindSpore-1/ms-code-195
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/2023-MindSpore-1/ms-code-201
https://github.com/2023-MindSpore-1/ms-code-202
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/2023-MindSpore-1/ms-code-206
https://github.com/2023-MindSpore-1/ms-code-207
https://github.com/2023-MindSpore-1/ms-code-208
https://github.com/2023-MindSpore-1/ms-code-21
MnasNet: Platform-Aware Neural Architecture Search for Mobile
https://github.com/2023-MindSpore-1/ms-code-210/tree/main/cnn_direction_model
https://github.com/2023-MindSpore-1/ms-code-211/tree/main/Deepsort
https://github.com/2023-MindSpore-1/ms-code-211/tree/main/detr
https://github.com/2023-MindSpore-1/ms-code-212/tree/main/EfficientDet_d0
https://github.com/2023-MindSpore-1/ms-code-212/tree/main/efficientnet-b0
An Efficient and Scalable Deep Learning Approach for Road Damage Detection
https://github.com/2023-MindSpore-1/ms-code-213/tree/main/EGnet
https://github.com/2023-MindSpore-1/ms-code-213/tree/main/FCANet
https://github.com/2023-MindSpore-1/ms-code-213/tree/main/FaceAttribute
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.