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General Classification

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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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/Jastot/Rodinka_Neural_Network

Going Deeper with Convolutions

https://github.com/JavierAntoran/pictocatcher

Going Deeper with Convolutions

https://github.com/Javihaus/Auto-ML-app-with-dash

XGBoost: A Scalable Tree Boosting System

https://github.com/JayKumarr/Fake-Review-Detection

Fake Review Detection Using Behavioral and Contextual Features

https://github.com/JeansonYang/VGG16-MindSpore

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/Jeff860530/ADDA

Adversarial Discriminative Domain Adaptation

https://github.com/JeffCHEN2017/WSSTG

Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset

https://github.com/JennyVanessa/Paddle-GHM

Gradient Harmonized Single-stage Detector

https://github.com/JeonMinkyu/MAML_Pytorch

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

https://github.com/JepsonWong/CNN_Visualization

Object Detectors Emerge in Deep Scene CNNs

https://github.com/JermXT/NMEPhw6

Unsupervised Representation Learning by Predicting Image Rotations

https://github.com/JerryKwon/melon_plylst_continuation

Convolutional Recurrent Neural Networks for Music Classification

https://github.com/Jerryten/model_nlp

Convolutional Neural Networks for Sentence Classification

https://github.com/JherezTaylor/hatespeech_codewords

Surfacing contextual hate speech words within social media

https://github.com/JiabenLi/rgcn_paddlepaddle

Modeling Relational Data with Graph Convolutional Networks

https://github.com/JiachuanDENG/CNN-Textual-RegressionModel-for-commodity-price-prediction

Convolutional Neural Networks for Sentence Classification

https://github.com/JiachuanDENG/Pytorch-CNN-Textual-RegressionModel-for-commodity-price-prediction

Convolutional Neural Networks for Sentence Classification

https://github.com/JianGoForIt/YellowFin_Pytorch

Tying Word Vectors and Word Classifiers: A Loss Framework for Language Modeling

https://github.com/JiaxiongQ/DeepBlindness

DeepBlindness: Fast Blindness Map Estimation and Blindness Type Classification for Outdoor Scene from Single Color Image

https://github.com/JinLi711/Attention-Augmented-Convolution

CBAM: Convolutional Block Attention Module

https://github.com/JinLi711/Convolution_Variants

CBAM: Convolutional Block Attention Module

https://github.com/JitindraFartiyal/Object-Detection

YOLO9000: Better, Faster, Stronger

https://github.com/Jllamoza/bbva_attrition

Distributed and parallel time series feature extraction for industrial big data applications

https://github.com/Jllamoza/bbva_attrition_FRESH

Distributed and parallel time series feature extraction for industrial big data applications

https://github.com/Jmak12/Iris1

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

https://github.com/Jmkernes/PAR-Transformer-XL

Categorical Reparameterization with Gumbel-Softmax

https://github.com/JoegameZhou/Levit

LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference

https://github.com/JohnGiorgi/compact-multi-head-self-attention-pytorch

Low Rank Factorization for Compact Multi-Head Self-Attention

https://github.com/JohnKurian/R2D2

Reasoning on Knowledge Graphs with Debate Dynamics

https://github.com/JohnMBrandt/capsule-attention-networks

Spatio-temporal crop classification of low-resolution satellite imagery with capsule layers and distributed attention

https://github.com/Johnnylyu/Text-Mining-and-Classification-for-Attain

Convolutional Neural Networks for Sentence Classification

https://github.com/Jongchan/attention-module

CBAM: Convolutional Block Attention Module

https://github.com/Jopapy19/CNN-App

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/Joppewouts/belabBERT

Text-based classification of interviews for mental health -- juxtaposing the state of the art

https://github.com/Jopyth/BMXNet

XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks

https://github.com/JosephElHachem/GradCam

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

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