Medical Image Classification
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Medical Image Classification is a task in medical image analysis that involves classifying medical images, such as X-rays, MRI scans, and CT scans, into different categories based on the type of image or the presence of specific structures or diseases. The goal is to use computer algorithms to automatically identify and classify medical images based on their content, which can help in diagnosis, treatment planning, and disease monitoring.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/TravisLeeTS/grabcvchallenge
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/TrevorIkky/RegNet
https://github.com/UESBTC/DenseNet-Tensorflow
https://github.com/UnofficialJuliaMirror/DeepMark-deepmark
https://github.com/UnofficialJuliaMirrorSnapshots/DeepMark-deepmark
https://github.com/Vamshi399/CarND-Vehicle-Detection
https://github.com/VamsiKrishna1211/gender_age-detection
https://github.com/VhalPurohit/290s
https://github.com/VinayBN8997/CIFAR-10-object-detection
https://github.com/VinayBN8997/ResNet-CIFAR10
https://github.com/VinayBhupalam/melanoma-detection
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/ViswanathaReddyGajjala/EfficientNet-RetinaNet
https://github.com/Westlake-AI/openmixup
https://github.com/WonJunPark/Efficientnet
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/Yeeun-Lee/parrot_proj1
https://github.com/Yeeun-Lee/parrot_vision_competition
https://github.com/YerevaNN/DIIN-in-Keras
https://github.com/YixuanLi/densenet-tensorflow
https://github.com/YudeWang/UNet-Satellite-Image-Segmentation
https://github.com/Zachdr1/CNNs
https://github.com/ZackPashkin/YOLOv3-EfficientNet-EffYolo
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/abaietto/neural_ode_classification
https://github.com/abhuse/pytorch-efficientnet
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/abuchin/resnet_sign
https://github.com/aby2s/sharpmask
https://github.com/adldotori/ResNet
https://github.com/agassi4013/Log-DenseNet-Tensorflow
https://github.com/aimbsg/EVA4_S15
https://github.com/ajaystar8/PDRUNet-PyTorch
https://github.com/ajithvallabai/getsetgo_keras-beginner
https://github.com/akamaster/pytorch_resnet_cifar10
https://github.com/akar5h/Image-Recognition-with-CNN-and-Transfer-Learning-ResNet101
https://github.com/akhadangi/EM-net
https://github.com/akommini/Spoken-Numeric-Digit-detection
https://github.com/alalagong/LEDNet
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.