https://github.com/gauthamkrishna-g/ActiveHARNet
ActiveHARNet: Towards On-Device Deep Bayesian Active Learning for Human Activity Recognition
Papers with Code 아카이브
Human Activity Recognition
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Classify various human activities
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/guillaume-chevalier/LSTM-Human-Activity-Recognition
Deep Residual Bidir-LSTM for Human Activity Recognition Using Wearable Sensors
https://github.com/ibrahimalimetin/HDAD-iGAV-Dataset-and-its-Benchmarking-GUI-with-Deep-Learning-Techniques-for-HAR
Deep Residual Bidir-LSTM for Human Activity Recognition Using Wearable Sensors
https://github.com/manish-vi/Human-Activity-Recognition
Understanding and Improving Deep Neural Network for Activity Recognition
https://github.com/manu-vishwakarma/human-activity-detection
Understanding and Improving Deep Neural Network for Activity Recognition
https://github.com/microsoft/qlib/tree/main/examples/benchmarks/ADARNN
https://github.com/miladvazan/LDA-MLP-SVM-SGD
https://github.com/mmalekzadeh/motion-sense
DANA: Dimension-Adaptive Neural Architecture for Multivariate Sensor Data
https://github.com/nassimmokhtari/Enhanced-Spatio-Temporal-Image-Encoding
https://github.com/nassimmokhtari/Spatio-Temporal-Image-Encoding
https://github.com/piergiaj/latent-subevents
Learning Latent Sub-events in Activity Videos Using Temporal Attention Filters
https://github.com/qiwang233/dailydvs-200
HARDVS: Revisiting Human Activity Recognition with Dynamic Vision Sensors
https://github.com/realcrane/SMART
Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box Attack
https://github.com/rlleshi/sensor-har
Human Activity Recognition from Wearable Sensor Data Using Self-Attention
https://github.com/sair-lab/ni-slam
https://github.com/sdimi/cardiofitness
Learning Generalizable Physiological Representations from Large-scale Wearable Data
https://github.com/toytiny/radarocc
milliFlow: Scene Flow Estimation on mmWave Radar Point Cloud for Human Motion Sensing
https://github.com/wang-chen/correlation_flow
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.