Transfer learning and its extensive appositeness in human activity recognition: A survey
A Ray, MH Kolekar - Expert Systems with Applications, 2024 - Elsevier
In this competitive world, the supervision and monitoring of human resources are primary
and necessary tasks to drive context-aware applications. Advancement in sensor and …
and necessary tasks to drive context-aware applications. Advancement in sensor and …
[HTML][HTML] An artificial intelligence framework on software bug triaging, technological evolution, and future challenges: A review
NK Nagwani, JS Suri - … Journal of Information Management Data Insights, 2023 - Elsevier
The timely release of defect-free software and the optimization of development costs depend
on efficient software bug triaging (SBT) techniques. SBT can also help in managing the vast …
on efficient software bug triaging (SBT) techniques. SBT can also help in managing the vast …
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …
large amount of data to achieve exceptional performance. Unfortunately, many applications …
Multi-hop graph pooling adversarial network for cross-domain remaining useful life prediction: A distributed federated learning perspective
Accurate remaining useful life (RUL) prediction has gained increasing attention in modern
maintenance management. Considering the data privacy requirements of distributed multi …
maintenance management. Considering the data privacy requirements of distributed multi …
Tracking floor eggs with machine vision in cage-free hen houses
Some of the major restaurants and grocery chains in the United States have pledged to buy
cage-free (CF) eggs only by 2025 or 2030. While CF house allows hens to perform more …
cage-free (CF) eggs only by 2025 or 2030. While CF house allows hens to perform more …
AI-driven behavior biometrics framework for robust human activity recognition in surveillance systems
The integration of artificial intelligence (AI) into human activity recognition (HAR) in smart
surveillance systems has the potential to revolutionize behavior monitoring. These systems …
surveillance systems has the potential to revolutionize behavior monitoring. These systems …
Cyber-physical system security based on human activity recognition through IoT cloud computing
Cyber-physical security is vital for protecting key computing infrastructure against cyber
attacks. Individuals, corporations, and society can all suffer considerable digital asset losses …
attacks. Individuals, corporations, and society can all suffer considerable digital asset losses …
A review of video-based human activity recognition: theory, methods and applications
Video-based human activity recognition (HAR) is an important task in many fields, such as
healthcare monitoring, video surveillance, and sports analysis. This review paper aims to …
healthcare monitoring, video surveillance, and sports analysis. This review paper aims to …
Few-shot learning-based human behavior recognition model
Scope The challenges of human behavior recognition based on sensor data often require
addressing the needs of various new users in real-world situations, which leads to difficulties …
addressing the needs of various new users in real-world situations, which leads to difficulties …
Transition-aware human activity recognition using an ensemble deep learning framework
Understanding human activities in daily life is of utmost importance, especially in the context
of personalized and adaptive ubiquitous learning. Although existing HAR systems perform …
of personalized and adaptive ubiquitous learning. Although existing HAR systems perform …