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General Classification
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Algorithms trying to solve the general task of classification.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/evrog/PunFields
공식 코드https://github.com/expertailab/Is-BERT-self-attention-a-feature-selection-method
공식 코드Classifying Scientific Publications with BERT -- Is Self-Attention a Feature Selection Method?
https://github.com/fabioperez/skin-data-augmentation
공식 코드https://github.com/fabsig/GradientNewtonBoosting
공식 코드Gradient and Newton Boosting for Classification and Regression
https://github.com/fabsig/KTBoost
공식 코드Gradient and Newton Boosting for Classification and Regression
https://github.com/fabvio/Cascade-LD
공식 코드https://github.com/fabvio/TuSimple-lane-classes
공식 코드https://github.com/facebookresearch/FixRes
공식 코드https://github.com/facebookresearch/ImageNet-Adversarial-Training
공식 코드https://github.com/facebookresearch/LeViT
공식 코드LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference
https://github.com/facebookresearch/MLDoc
공식 코드A Corpus for Multilingual Document Classification in Eight Languages
https://github.com/facebookresearch/Needles-in-Haystacks
공식 코드Needles in Haystacks: On Classifying Tiny Objects in Large Images
https://github.com/facebookresearch/ResNeXt
공식 코드Aggregated Residual Transformations for Deep Neural Networks
https://github.com/facebookresearch/SEAL_OGB
공식 코드Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning
https://github.com/facebookresearch/SentEval
공식 코드SentEval: An Evaluation Toolkit for Universal Sentence Representations
https://github.com/facebookresearch/SlowFast
공식 코드https://github.com/facebookresearch/TimeSformer
공식 코드Is Space-Time Attention All You Need for Video Understanding?
https://github.com/facebookresearch/VMZ
공식 코드Video Classification with Channel-Separated Convolutional Networks
https://github.com/facebookresearch/adversarial_image_defenses
공식 코드https://github.com/facebookresearch/barlowtwins
공식 코드Barlow Twins: Self-Supervised Learning via Redundancy Reduction
https://github.com/facebookresearch/classifier-balancing
공식 코드Decoupling Representation and Classifier for Long-Tailed Recognition
https://github.com/facebookresearch/deit
공식 코드ResMLP: Feedforward networks for image classification with data-efficient training
https://github.com/facebookresearch/fastText
공식 코드https://github.com/facebookresearch/maskrcnn-benchmark
공식 코드Is Heuristic Sampling Necessary in Training Deep Object Detectors?
https://github.com/facebookresearch/mmbt
공식 코드Supervised Multimodal Bitransformers for Classifying Images and Text
https://github.com/facebookresearch/mmf
공식 코드The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes
https://github.com/facebookresearch/momi
공식 코드Generate, Filter, and Rank: Grammaticality Classification for Production-Ready NLG Systems
https://github.com/facebookresearch/multigrain
공식 코드MultiGrain: a unified image embedding for classes and instances
https://github.com/facebookresearch/parcus
공식 코드https://github.com/facebookresearch/randsent
공식 코드No Training Required: Exploring Random Encoders for Sentence Classification
https://github.com/facebookresearch/supervised-hashing-baselines
공식 코드https://github.com/fadymedhat/MCLNN
공식 코드Automatic Classification of Music Genre using Masked Conditional Neural Networks
https://github.com/fadymedhat/YorNoise
공식 코드Masked Conditional Neural Networks for Environmental Sound Classification
https://github.com/fahadsohrab/essvdd
공식 코드https://github.com/fahadsohrab/gessvdd
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.