Papers with Code 아카이브
LIDAR Semantic Segmentation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yueyongjiao/attention_is_all_you_need_pytorch
https://github.com/yuhangT/tf_bert
https://github.com/yuhsijen/Object-Detector
https://github.com/yuhsuanlin23130/Vehicle-Detection-2019
https://github.com/yumoh/speech-keras
https://github.com/yuqj1990/caffe_deeplearning_train
https://github.com/yuqj1990/caffe_train
https://github.com/yuqj1990/deepano_face_train
https://github.com/yuqj1990/deepano_train
https://github.com/yuqj1990/face_train
https://github.com/yydai/bert_test
https://github.com/zankner/Transformer
https://github.com/zapplea/bert
https://github.com/zer0sh0t/artificial_intelligence/tree/master/transformer
https://github.com/zhang-huihui/git-repository
https://github.com/zhangbo2008/best_pytorch_transformer
https://github.com/zhreshold/mxnet-ssd
https://github.com/zhuyi55/week9
https://github.com/zipeiyang/DeepSpeechRecognition
https://github.com/zjZSTU/SSD
https://github.com/zoeyuchao/caffe-ssd
https://github.com/zqplgl/caffe
https://github.com/zsweet/BERT_zsw
https://github.com/zysite/post
https://gitlab.com/birder/birder
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.