In order to achieve collision-free path planning in complex environment, Munchausen deep
Q-learning network (M-DQN) is applied to mobile robot to learn the best decision. On the …

Accurate and reliable capacity estimation is crucial for lithium-ion batteries to operate safely
and stably. However, the extraction steps of health indicators (HIs) limit the feasibility and …

Learning from streaming tasks leads a model to catastrophically erase unique experiences it
absorbs from previous episodes. While regularization techniques such as LWF, SI, EWC …

Cross-database micro-expression recognition (CDMER) is a difficult task, where the target
(testing) and source (training) samples come from different micro-expression (ME) …

In milling processing, the wear state of the tool has an essential influence on the processing
quality. The machining process is not continuous in the cycloid milling process, and the …

In this article, the futuristically possible human (commander)-robot (soldier) interaction (HRI)
based on effective hand gesture recognition is discussed. As methodologically, Leap Motion …

Deep learning provides an effective way for automatic classification of cardiac arrhythmias,
but in clinical decision-making, pure data-driven methods working as black-boxes may lead …

With the surge of ChatGPT, the use of large models has significantly increased, rapidly rising
to prominence across the industry and sweeping across the internet. This article is a …

The instability is shown in the existing methods of representation learning based on
Euclidean distance under a broad set of conditions. Furthermore, the scarcity and high cost …

Density-based directed distances—particularly known as divergences—between probability
distributions are widely used in statistics as well as in the adjacent research fields of …