In incremental learning, replaying stored samples from previous tasks together with current
task samples is one of the most efficient approaches to address catastrophic forgetting …

This paper investigates data-free class-incremental learning (DFCIL) for hand gesture
recognition from 3D skeleton sequences. In this class-incremental learning (CIL) setting …

In incremental object detection, knowledge distillation has been proven to be an effective
way to alleviate catastrophic forgetting. However, previous works focused on preserving the …

In incremental learning, replaying stored samples from previous tasks together with current
task samples is one of the most efficient approaches to address catastrophic forgetting …

Hand gesture recognition (HGR) is essential for human-machine interaction. Although the
existing solutions achieve good performance in specific tasks, they still face challenges …

Gesture recognition using sensor data generated from mobile devices is used as a crucial
part of human-computer interaction systems. These applications must allow users to easily …

Deep Learning has shown great success in reshaping medical imaging, yet it faces
numerous challenges hindering widespread application. Issues like catastrophic forgetting …

Sensor-based gesture recognition on mobile devices is critical to human–computer
interaction, enabling intuitive user input for various applications. However, current …

Hand gesture recognition (HGR) plays a vital role in human-computer interaction. The
integration of high-density surface electromyography (HD-sEMG) and deep neural networks …

Abstract Machine Learning-based Sign Language Dictionaries recognize a sign performed
in front of a camera and return the most probable written language word. Due to the scarce …