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General Classification

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평가표

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보존된 평가 기록

19

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/facebookresearch/pytext

Convolutional Neural Networks for Sentence Classification

https://github.com/facebookresearch/pytorchvideo

SlowFast Networks for Video Recognition

https://github.com/facebookresearch/semi-supervised-ImageNet1K-models

Billion-scale semi-supervised learning for image classification

https://github.com/facebookresearch/stochastic_gradient_push

Stochastic Gradient Push for Distributed Deep Learning

https://github.com/facebookresearch/svoice

Single channel voice separation for unknown number of speakers under reverberant and noisy settings

https://github.com/facebookresearch/vissl

Unsupervised Representation Learning by Predicting Image Rotations

https://github.com/facebookresearch/visual-counterfactuals

Counterfactual Visual Explanations

https://github.com/facundoq/transformational_measures_experiments

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/fagonzalezo/qmc

Supervised Learning with Quantum Measurements

https://github.com/fairlearn/fairlearn

Equality of Opportunity in Supervised Learning

https://github.com/faizanahemad/facebook-hateful-memes

The Relative Performance of Ensemble Methods with Deep Convolutional Neural Networks for Image Classification

https://github.com/fanconic/this-does-not-look-like-that

This Looks Like That: Deep Learning for Interpretable Image Recognition

https://github.com/fangrouli/Document-embedding-generation-models

Convolutional Neural Networks for Sentence Classification

https://github.com/fanzhenliu/dagad

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/farbodtaymouri/BERT-GAN

An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction

https://github.com/farhanhubble/omniglot

The Omniglot challenge: a 3-year progress report

https://github.com/faridSam/srn

Selective Refinement Network for High Performance Face Detection

https://github.com/farshidrayhanuiu/CUSBoost

CUSBoost: Cluster-based Under-sampling with Boosting for Imbalanced Classification

https://github.com/fastforwardlabs/learning-to-learn

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/fastrapp/fastr-android-app

Learning to detect dysarthria from raw speech

https://github.com/fatLime/Predict-Lung-Disease

ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases

https://github.com/fbcotter/scatnet_learn

Invariant Scattering Convolution Networks

https://github.com/fbenites/sklearn-hierarchical-classification

Evaluation Measures for Hierarchical Classification: a unified view and novel approaches

https://github.com/fcUalberta/UAlberta-Multimedia-Masters-Program-Interpretable-AI-Part_1_2

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

https://github.com/fcakyon/sahi-benchmark

Varifocal-Net: A Chromosome Classification Approach using Deep Convolutional Networks

https://github.com/fchollet/deep-learning-models

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/feedzai/fairgbm

Equality of Opportunity in Supervised Learning

https://github.com/feixuetuba/inpainting

Partial Convolution based Padding

https://github.com/feixuetuba/inpating

Partial Convolution based Padding

https://github.com/felix-laumann/Bayesian_CNN_ContinualLearning

Weight Uncertainty in Neural Networks

https://github.com/felixopolka/deep-gaussian-process

Doubly Stochastic Variational Inference for Deep Gaussian Processes

https://github.com/fenghz/cosda

Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer

https://github.com/ferhatkkochan/deeplearning-notes

A systematic study of the class imbalance problem in convolutional neural networks

https://github.com/ferryjul/fairCORELS

Learning Fair Rule Lists

https://github.com/fescobar96/Image-Noise-Removal

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

https://github.com/fferroni/fisher_vector_classifier

3D Point Cloud Classification and Segmentation using 3D Modified Fisher Vector Representation for Convolutional Neural Networks

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.