Papers with Code 아카이브

General Classification

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

11

보존된 평가 기록

19

코드

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

https://github.com/Nikhil9786/Implemetation-of-VGG16-ResNet18-InceptionV2-on-Cifar100

Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning

https://github.com/NikhilBadami/YogiAI

Yoga-82: A New Dataset for Fine-grained Classification of Human Poses

https://github.com/NikhilVanapalli/Gesture-Recognition-for-HCI

EMNIST: an extension of MNIST to handwritten letters

https://github.com/NikoKVCS/proximity_forest

Proximity Forest: An effective and scalable distance-based classifier for time series

https://github.com/Nim-NLP/fastText

Bag of Tricks for Efficient Text Classification

https://github.com/Niousha12/Text_Classification_via_GNN

Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks

https://github.com/Nirvanabc/sentence_classification

Convolutional Neural Networks for Sentence Classification

https://github.com/Niteeshaballa/fastai-practice

Visualizing and Understanding Convolutional Networks

https://github.com/Nithesh5/torch-adni-bagging-with-attentional

CBAM: Convolutional Block Attention Module

https://github.com/Nithesh5/torch-adni-bootstrap-with-attentional

CBAM: Convolutional Block Attention Module

https://github.com/NivNayman/XNAS

DARTS: Differentiable Architecture Search

https://github.com/Nnra/AIAproject

SoundNet: Learning Sound Representations from Unlabeled Video

https://github.com/Nogimon/FlyNet

Segmentation of Drosophila Heart in Optical Coherence Microscopy Images Using Convolutional Neural Networks

https://github.com/Noodles-321/OralScreen

A Deep Learning based Pipeline for Efficient Oral Cancer Screening on Whole Slide Images

https://github.com/Nov05/Genre-Fiction-Classification

Which Encoding is the Best for Text Classification in Chinese, English, Japanese and Korean?

https://github.com/O1sims/reversible-residual-network

The Reversible Residual Network: Backpropagation Without Storing Activations

https://github.com/OFRIN/Tensorflow_Improving_Pairwise_Ranking_for_Multi-label_Image_Classification

Improving Pairwise Ranking for Multi-label Image Classification

https://github.com/OML-Team/open-metric-learning

In Defense of the Triplet Loss for Person Re-Identification

https://github.com/OPAYA/Transformer

A Structured Self-attentive Sentence Embedding

https://github.com/OanaIgnat/i3d_keras

The Kinetics Human Action Video Dataset

https://github.com/Octavio-Pappalardo/MAML_for_RL_pytorch

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

https://github.com/Octavio-Pappalardo/unsupervised-pretraining-via-self-classification

Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks

https://github.com/OdysseasKr/online-nilm

Neural NILM: Deep Neural Networks Applied to Energy Disaggregation

https://github.com/Oguzhanercan/Vision-Transformers

Visual Transformers: Token-based Image Representation and Processing for Computer Vision

https://github.com/Oichii/resnet3D_pulse

Would Mega-scale Datasets Further Enhance Spatiotemporal 3D CNNs?

https://github.com/Oliver-jiang/Tensor-decomposition-pytorch

Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition

https://github.com/OlivierAlgoet/Tensorflow2-GMM

Categorical Reparameterization with Gumbel-Softmax

https://github.com/Omerktn/fastText-iterative

Bag of Tricks for Efficient Text Classification

https://github.com/OneRaynyDay/xnornet

XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks

https://github.com/Onysuke/chainer-grad-cam

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

https://github.com/OpenXAIProject/LRP_for_LSTM_Korean_dataset

Explaining NonLinear Classification Decisions with Deep Taylor Decomposition

https://github.com/OpenXAIProject/UncertintyAttention_DropMax

DropMax: Adaptive Variational Softmax

https://github.com/OptimusPrimus/dcase2020_workshop

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification

https://github.com/OrkhanHI/Grab-AI-Computer-Vision-Challenge

A Systematic Evaluation of Recent Deep Learning Architectures for Fine-Grained Vehicle Classification

https://github.com/OsvaldN/APS360_Project

Empirical Evaluation of Rectified Activations in Convolutional Network

https://github.com/OzHsu23/chineseocr

COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images

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