Visual inspection of defective tires post-production is vital for human safety, as faulty tires can lead to explosions, accidents, and loss of life. With the advancement of technology, transfer learning (TL) plays an influential role in many …

Neuromorphic hardware has become hotspot in the field of brain-like computing due to its advantages. However, the presence of external noise imposes challenges with respect to maintaining normal function of neuromorphic hardware. Biological brains …

Infrared and visible image fusion techniques have emerged as powerful methods to harness the unique advantages of diverse sensors, resulting in improved image quality through the preservation of complementary and redundant information from the …

Intent detection and slot filling are two crucial tasks for spoken language understanding, and they are closely related. The accuracy of spoken language understanding depends strongly on the effectiveness of the interaction between intent and slot …

Large language models (LLMs) have demonstrated promising in-context learning capabilities, especially with instructive prompts. However, recent studies have shown that existing large models still face challenges in specific information extraction …

E-waste generation has broadly increased worldwide and is called intense pressure on sustainable practice implementation firms by recycling and redesigning the products. Thus, e-waste operation management in developed countries like the UK has …

This paper addressed the finite-time multistability of a Caputo fractional order multidirectional associative memory neural network (FMAMNN) with multiple orders, where the fractional orders are not limited to 0 to 1. There are three main …

This paper describes and evaluates the performance of a learning classifier system (lcs) inspired algorithm called Temporal Reinforcement And Classification Architecture (traca) on maze navigation tasks which contain hidden state. The evaluation …

Autism spectrum disorder (ASD) is a neurological condition characterized by impaired functional connectivity (FC) networks in the brain. There are several brain networks associated with ASD that have been studied for ASD diagnosis, but the results …

The inspection and diagnosis of building engineering involve rail surface defect detection, which plays a crucial role in assessing the quality of railway tracks. However, achieving accurate detection remains a significant challenge for …

Heterogeneous domain adaptation (HDA) aims at facilitating the target model training by leveraging knowledge from the heterogeneous source domain. HDA is a challenging problem since the domains are not consistent in not only data distribution but …

Pneumatic actuators exhibit significant potential across various applications owing to their compliance, yet achieving precise motion control remains challenging due to rate-dependent and asymmetric hysteresis. While the Prandtl–Ishlinskii model …

In recent years, self-supervised representation learning for skeleton-based action recognition has achieved remarkable results using skeleton sequences with the advance of contrastive learning methods. However, existing methods often overlook the …

Data are an essential component for building machine learning models. Linearly separable high-quality data are conducive to building efficient classification models. However, the collected dataset is not of high quality, and the number of …

Graph neural networks (GNNs) are powerful tools for data mining on graph-structured data in various domains, such as social science, finance, and biology. However, most existing GNNs operate in Euclidean space and may fail to preserve the …

This work focuses on bringing state-of-the-art artificial intelligence and deep reinforcement learning to the manufacturing of semiconductor devices. The main goal of this research is to lay down the foundation of an end-to-end system for …

This research delves into the intricate connection between self-attention mechanisms in large-scale pre-trained language models, like BERT, and human gaze patterns, with the aim of harnessing gaze information to enhance the performance of natural …

This paper proposes a hybrid Modified Coronavirus Herd Immunity Aquila Optimization Algorithm (MCHIAO) that compiles the Enhanced Coronavirus Herd Immunity Optimizer (ECHIO) algorithm and Aquila Optimizer (AO). As one of the competitive …

Harris Hawks optimization (HHO) algorithm was a powerful metaheuristic algorithm for solving complex problems. However, HHO could easily fall within the local minimum. In this paper, we proposed an improved Harris Hawks optimization (IHHO) …