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General Classification

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보존된 평가 기록

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코드

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

https://github.com/mohamad-m2/federated-learning

Federated Visual Classification with Real-World Data Distribution

https://github.com/mohamedameen93/German-Traffic-Sign-Classification-Using-TensorFlow

ADADELTA: An Adaptive Learning Rate Method

https://github.com/mohammadreza-Banaei73/INLP_neural_practical_session

Bag of Tricks for Efficient Text Classification

https://github.com/mohith-sakthivel/mine-pytorch

MINE: Mutual Information Neural Estimation

https://github.com/mohitiitb/DummyRepo

EMNIST: an extension of MNIST to handwritten letters

https://github.com/mohitiitb/NeuralNetworkVerification_GlobalRobustness

EMNIST: an extension of MNIST to handwritten letters

https://github.com/mojave-pku/uniprompt

The Multilingual Amazon Reviews Corpus

https://github.com/monkey0head/Domain_Adaptation_thesis

Domain-Adversarial Training of Neural Networks

https://github.com/monologg/JointBERT

BERT for Joint Intent Classification and Slot Filling

https://github.com/monologg/R-BERT

Enriching Pre-trained Language Model with Entity Information for Relation Classification

https://github.com/monsta-hd/boltzmann-machines

How far can we go without convolution: Improving fully-connected networks

https://github.com/moradisten/KNN-LB

Elastic bands across the path: A new framework and methods to lower bound DTW

https://github.com/moradisten/PForests

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

https://github.com/moradisten/ProximityForests-python

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

https://github.com/morehovschi/drumsep

Singing Voice Separation Using a Deep Convolutional Neural Network Trained by Ideal Binary Mask and Cross Entropy

https://github.com/morphocluster/morphocluster

MorphoCluster: Efficient Annotation of Plankton images by Clustering

https://github.com/morrisxu-driving/video-music_cross-modal_retrival

CNN Architectures for Large-Scale Audio Classification

https://github.com/moserle/TSJS-Grad-CAM

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

https://github.com/moseslichten/TAFSSL

TAFSSL: Task-Adaptive Feature Sub-Space Learning for few-shot classification

https://github.com/moskomule/eve.pytorch

Eve: A Gradient Based Optimization Method with Locally and Globally Adaptive Learning Rates

https://github.com/mostafaelhoushi/tensor-decompositions

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

https://github.com/mostafij-rahman/PyTorch-PrototypeDL

Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictions

https://github.com/moucheng2017/learning_morphological_perturbation_ssl

Semi-supervised semantic segmentation needs strong, varied perturbations

https://github.com/moucheng2017/mismatchssl

Semi-supervised semantic segmentation needs strong, varied perturbations

https://github.com/mr-bulb/DL_basic_github

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/mr-eggplant/eata

Tent: Fully Test-time Adaptation by Entropy Minimization

https://github.com/mr7495/oct-classification

Wise-SrNet: A Novel Architecture for Enhancing Image Classification by Learning Spatial Resolution of Feature Maps

https://github.com/mrahtz/learning-from-human-preferences

Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

https://github.com/mrateike/fair_minimonster

Equal Opportunity in Online Classification with Partial Feedback

https://github.com/mrazimi99/deep-packet

Deep Packet: A Novel Approach For Encrypted Traffic Classification Using Deep Learning

https://github.com/mrdbourke/tensorflow-deep-learning

PubMed 200k RCT: a Dataset for Sequential Sentence Classification in Medical Abstracts

https://github.com/mrmtn86/python1

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

https://github.com/mrtzh/whynot

Strategic Classification

https://github.com/ms8909/LipONet

LipNet: End-to-End Sentence-level Lipreading

https://github.com/ms96590/-

Evidential Deep Learning to Quantify Classification Uncertainty

https://github.com/ms96590/pytorch-classification-uncertainty

Evidential Deep Learning to Quantify Classification Uncertainty

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