Image Classification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 33
- 평가표
- 177
- 보존된 평가 기록
- 2,906
Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/endgameinc/malware_evasion_competition
https://github.com/engelnico/point-transformer
https://github.com/engichang1467/MLP-Mixer-Reimplementation
https://github.com/engichang1467/kan-mixer
https://github.com/ensta-u2is/deeplabv3plus-muad-pytorch
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
https://github.com/ensta-u2is/torch-uncertainty
https://github.com/enzomuschik/distilfnd
https://github.com/eogussla12/Shufflenet_CIFAR10_Pytorch
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/epfl-dlab/invariant-language-models
https://github.com/epfl-ml-reproducers/subspace-attack-reproduction
https://github.com/epoc88/PFLD_68pts_Pytorch_2020
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/eps696/aphantasia
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/epsilon-deltta/ssd_guillotine
https://github.com/erbloo/dr
Enhancing Cross-task Black-Box Transferability of Adversarial Examples with Dispersion Reduction
https://github.com/eric-erki/IdenProf
https://github.com/eric-erki/darknet
https://github.com/eric-erki/darknetAB
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
https://github.com/eric-erki/yolov3
https://github.com/eric-mitchell/mend
https://github.com/eric-mitchell/serac
https://github.com/erichson/noisy_mixup
https://github.com/ericleixd/mlpMixer-MindSpore
https://github.com/ericyinyzy/vlattack
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/eriklindernoren/Keras-GAN
https://github.com/eriklindernoren/PyTorch-GAN
https://github.com/erlendd/ddan
https://github.com/ermolenkodev/da-ssd
https://github.com/ermuur/darknet
https://github.com/ernie1/pi-nas
Momentum Contrast for Unsupervised Visual Representation Learning
https://github.com/errec-sun/mnist
https://github.com/escorciav/roi_pooling
DiracNets: Training Very Deep Neural Networks Without Skip-Connections
https://github.com/eshoyuan/taop2021-3rd-solution
https://github.com/espressif/esp-who
https://github.com/esraaelelimy/LRU
https://github.com/esslushy/AbstractArtGenerator
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.