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Deep Learning
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/fulviomascara/pytorch-cv
Facial Expression Recognition Research Based on Deep Learning
https://github.com/fznsakib/great-ape-behaviour-detector
https://github.com/gabriel-sgama/semantic-superpoint
Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics
https://github.com/gabrielkasmi/pypvroof
https://github.com/ganeshdg95/leveraging-adversarial-examples-to-quantify-membership-information-leakage
https://github.com/gcunhase/embracebert
EmbraceNet: A robust deep learning architecture for multimodal classification
https://github.com/geometric-intelligence/topobenchmark
TopoBench: A Framework for Benchmarking Topological Deep Learning
https://github.com/ghodouss/Aperio
Deep CNN Frame Interpolation with Lessons Learned from Natural Language Processing
https://github.com/giallo41/tensorflow_dlrm
Deep Learning Recommendation Model for Personalization and Recommendation Systems
https://github.com/gift-surg/fetal_brain_seg
https://github.com/giladcohen/sif_mi_attack
https://github.com/gilgameshxyz123/dragon-alpha
Dragon-Alpha&cu32: A Java-based Tensor Computing Framework With its High-Performance CUDA Library
https://github.com/gina-santana/American_Sign_Language
Xception: Deep Learning with Depthwise Separable Convolutions
https://github.com/gitboyzorro5/tensor2tensor
https://github.com/giuliomattolin/tsmixer-pytorch
TSMixer: An All-MLP Architecture for Time Series Forecasting
https://github.com/glouppe/info8010-deep-learning
Understanding deep learning requires rethinking generalization
https://github.com/gmalivenko/pynet-v2
Replacing Mobile Camera ISP with a Single Deep Learning Model
https://github.com/gmarceca/UTime-PlasmaStates
U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging
https://github.com/gmooers96/CBRAIN-CAM
Deep learning to represent sub-grid processes in climate models
https://github.com/godpgf/scarn
Fast, Accurate, and Lightweight Super-Resolution with Cascading Residual Network
https://github.com/gofynd/mildnet
https://github.com/gordicaleksa/pytorch-GAT
Fake News Detection on Social Media using Geometric Deep Learning
https://github.com/gotbutchi/Coderschool-Machine-Learning-Final-Project
Deep Learning-Based Automatic Downbeat Tracking: A Brief Review
https://github.com/gregzanotti/dlsa-public
https://github.com/gridgentoo/UberHorovod
Horovod: fast and easy distributed deep learning in TensorFlow
https://github.com/grtzsohalf/SpeechNet-codebase
Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics
https://github.com/grwlf/galaxy-lang
https://github.com/guanhuaw/Bjork
MoDL: Model Based Deep Learning Architecture for Inverse Problems
https://github.com/guanjq/targetdiff
Generating 3D Molecules Conditional on Receptor Binding Sites with Deep Generative Models
https://github.com/guluguluhhhh/contrib/tree/37-2/application/multi-task-learning-using-uncertainty-to
Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics
https://github.com/guoheidanqq/deeplearningjeffheatonT81
https://github.com/gusye1234/Pytorch-HSIC-bottleneck
https://github.com/gyaansastra/DeepLab
Deep learning tools for the measurement of animal behavior in neuroscience
https://github.com/gylee1103/ELDNet
Deep Saliency with Encoded Low level Distance Map and High Level Features
https://github.com/gylee1103/SaliencyELD
Deep Saliency with Encoded Low level Distance Map and High Level Features
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.