Papers with Code 아카이브
2D Classification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/amittiwary42/target-detection-eeg-signals
https://github.com/amiyamandal-dev/pegasus
Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategies
https://github.com/amogh7joshi/engagement-detection
https://github.com/amogh7joshi/fer
https://github.com/amogh7joshi/plant-health-detection
https://github.com/amol-matkar/Face-Mask-Segmentation
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
https://github.com/amritasaha1812/pytorch-faster-rcnn
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/amshaker/swiftformer
EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision Applications
https://github.com/amy-tabb/aruco-pattern-write
Using cameras for precise measurement of two-dimensional plant features: CASS
https://github.com/anandjebakumar/unet
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/anant95/K_means-image-compression
Semantic Perceptual Image Compression using Deep Convolution Networks
https://github.com/ananyahjha93/swav
https://github.com/anastassia-b/neural-algorithm-artistic-style
https://github.com/anatolix/keras_Realtime_Multi-Person_Pose_Estimation
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/anbunathan/WikiHow-Semantic
https://github.com/andersonstra/mukea
OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge
https://github.com/andi611/Self-Supervised-Speech-Pretraining-and-Representation-Learning
Defense for Black-box Attacks on Anti-spoofing Models by Self-Supervised Learning
https://github.com/andreamazzitelli/ProjectNN
Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model
https://github.com/andreaslillevangbech/PortfolioManager-pytorch
Reinforcement-Learning based Portfolio Management with Augmented Asset Movement Prediction States
https://github.com/andreasveit/densenet-pytorch
https://github.com/andrewbo29/mtm-meta-learning-sa
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
https://github.com/andrewilyas/ens-adv-train-attack
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/andrewowens/multisensory
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/andrey1908/mmdetection
https://github.com/andrijazz/pruning
https://github.com/andrijdavid/clinical-brain-interface-2020
https://github.com/andy-yangz/writing_style_transfer
https://github.com/andycao1125/mambadm
https://github.com/anenbergb/Co-DETR-TensorRT
https://github.com/anfidthtn/HAC
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
https://github.com/angelvillar96/FaceEmoji
https://github.com/anguyen120/fake-news-in-time
Check-It: A Plugin for Detecting and Reducing the Spread of Fake News and Misinformation on the Web
https://github.com/anguyen8/sam
https://github.com/anh-nn01/Satellite-Imagery-to-Map-Translation-using-Pix2Pix-GAN-framework
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/anhkhoa039/Neural-Style-Transfer
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.