Fundamental Recognition of ADL Assessments Using Machine Learning Engineering-Reference-Cited by-同舟云学术

Fundamental Recognition of ADL Assessments Using Machine Learning Engineering

Published:2022-08-16 Issue: Volume: Page:
ISSN:
Container-title:2022 19th International Bhurban Conference on Applied Sciences and Technology (IBCAST)
language:
Short-container-title:

Author:

Batool Mouazma¹,Javeed Madiha¹

Affiliation:

1. Air University,Dept. of Computer Science,Islamabad,Pakistan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9989533/9990034/09990303.pdf?arnumber=9990303

Reference79 articles.

1. Students’ behavior mining in e-learning environment using cognitive processes with information technologies

2. Adaptive pose estimation for gait event detection using context?aware model and hierarchical optimization;akhter;JEET,2021

3. Multi-features descriptors for Human Activity Tracking and Recognition in Indoor-Outdoor Environments

4. Automatic human posture estimation for sport activity recognition with robust body parts detection and entropy markov model;amir;Multimedia Tools and Applications,2021

5. Scene Understanding and Recognition: Statistical Segmented Model using Geometrical Features and Gaussian Naïve Bayes

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. CABMNet: An adaptive two-stage deep learning network for optimized spatial and temporal analysis in fall detection;Biomedical Signal Processing and Control;2024-10

2. A robust multimodal detection system: physical exercise monitoring in long-term care environments;Frontiers in Bioengineering and Biotechnology;2024-08-08

3. Multi-sensors Fused IoT-based Home Surveillance via Bag of Visual and Motion Features;2023 International Conference on Communication, Computing and Digital Systems (C-CODE);2023-05-17

4. Deep Skeleton Modeling and Hybrid Hand-crafted Cues over Physical Exercises;2023 International Conference on Communication, Computing and Digital Systems (C-CODE);2023-05-17

5. Multi-Sensor-Based Action Monitoring and Recognition via Hybrid Descriptors and Logistic Regression;IEEE Access;2023