Papers with Code 아카이브

Brain Decoding

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크: 1
평가표: 2
보존된 평가 기록: 8

Motor Brain Decoding is fundamental task for building motor brain computer interfaces (BCI).

Progress in predicting finger movements based on brain activity allows us to restore motor functions and improve rehabilitation process of patients.

코드

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

https://github.com/xiangtaokong/tgbd

공식 코드

Toward Generalizing Visual Brain Decoding to Unseen Subjects

https://github.com/xiaoyao3302/unibrain

공식 코드

UniBrain: A Unified Model for Cross-Subject Brain Decoding

https://github.com/xqchen914/abat

공식 코드

Alignment-Based Adversarial Training (ABAT) for Improving the Robustness and Accuracy of EEG-Based BCIs

https://github.com/xuefeng-cs/erp

공식 코드

Entropy-Reinforced Planning with Large Language Models for Drug Discovery

https://github.com/yaricom/brainhash

공식 코드

Applying advanced machine learning models to classify electro-physiological activity of human brain for use in biometric identification

https://github.com/yi-ding-cs/LGG

공식 코드

LGGNet: Learning from Local-Global-Graph Representations for Brain-Computer Interface

https://github.com/yi-ding-cs/eeg-patchformer

공식 코드

Decoding Human Attentive States from Spatial-temporal EEG Patches Using Transformers

https://github.com/yihui-he/channel-pruning

공식 코드

Channel Pruning for Accelerating Very Deep Neural Networks

https://github.com/yjzhao19981027/datformer

공식 코드

Distortion-aware Transformer in 360° Salient Object Detection

https://github.com/yuanmingze/360OpticalFlow-TangentImages

공식 코드

360° Optical Flow using Tangent Images

https://github.com/yudongpan/tegan

공식 코드

Short-length SSVEP data extension by a novel generative adversarial networks based framework

https://github.com/yuliangguo/depth_any_camera

공식 코드

Depth Any Camera: Zero-Shot Metric Depth Estimation from Any Camera

https://github.com/yulongbonjour/see_through_their_minds

공식 코드

See Through Their Minds: Learning Transferable Neural Representation from Cross-Subject fMRI

https://github.com/zhangzjn/ocr-gan

공식 코드

Omni-frequency Channel-selection Representations for Unsupervised Anomaly Detection

https://github.com/zhengshuchen/hcfnet

공식 코드

HCF-Net: Hierarchical Context Fusion Network for Infrared Small Object Detection

https://github.com/ziyuey/cssstn

공식 코드

CSSSTN: A Class-sensitive Subject-to-subject Semantic Style Transfer Network for EEG Classification in RSVP Tasks

https://github.com/zjc062/mind-vis

공식 코드

Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision Decoding

https://gitlab.com/pierregtch/motor_embedding_benchmark

공식 코드

Transfer Learning between Motor Imagery Datasets using Deep Learning -- Validation of Framework and Comparison of Datasets

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