https://github.com/kwantommy/fgvc6-kaggle-cassava-classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
Papers with Code 아카이브
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/ky941122/darts-experiment
https://github.com/kyeongry/Autoencoders
https://github.com/kyeongsoo/indoor_localization
Low-effort place recognition with WiFi fingerprints using deep learning
https://github.com/kylemath/DeepEEG
Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks
https://github.com/kylemin/S3D
Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video Classification
https://github.com/kylitt/res
Rethinking Few-Shot Image Classification: a Good Embedding Is All You Need?
https://github.com/kynkaat/improved-precision-and-recall-metric
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/kyunghwan/darknet_v3
https://github.com/kyungsu-lee-ksl/ash
https://github.com/lRomul/argus-freesound
Learning Sound Event Classifiers from Web Audio with Noisy Labels
https://github.com/labmlai/annotated_deep_learning_paper_implementations
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
https://github.com/labouz/xai-pres-1
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
https://github.com/lacava/few
https://github.com/lackel/hierarchical_weighted_scl
https://github.com/lackel/sdc
Benchmarking Natural Language Understanding Services for building Conversational Agents
https://github.com/ladislasl/CNN_invar_rot
Learning rotation invariant convolutional filters for texture classification
https://github.com/laiviet/maml
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
https://github.com/lajanugen/S2V
An efficient framework for learning sentence representations
https://github.com/lalithjets/surgical_vqa
ResMLP: Feedforward networks for image classification with data-efficient training
https://github.com/laohur/LearnToCompareText
https://github.com/laohur/RelationNet
https://github.com/laramaktub/plant-classification-tf-train
https://github.com/larry0123du/Decompose-CNN
CP-decomposition with Tensor Power Method for Convolutional Neural Networks Compression
https://github.com/latte488/smth-smth-v2
The "something something" video database for learning and evaluating visual common sense
https://github.com/laugh12321/3D-Attention-Keras
https://github.com/lauraperge/blackbox-trading-CNN
Classification of Time-Series Images Using Deep Convolutional Neural Networks
https://github.com/layumi/Person-reID-verification
A Discriminatively Learned CNN Embedding for Person Re-identification
https://github.com/layumi/Person_reID_baseline_pytorch
https://github.com/layumi/University1652-Baseline
https://github.com/lazarotm/SVDCNN
Squeezed Very Deep Convolutional Neural Networks for Text Classification
https://github.com/lazyjek/image_feature_extract_virtualize
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
https://github.com/lbneon/research
EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks
https://github.com/lcylmhlcy/ResnetCrowd-Caffe
https://github.com/leaderj1001/Attention-Augmented-Conv2d
https://github.com/leaderj1001/Bag-of-MLP
ResMLP: Feedforward networks for image classification with data-efficient training
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.