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In this study, a novel Quantum Self-Attention Neural Network for Multi-Model Aerial Image Classification (QSANN-MAIC) is proposed. The objective of this paper is to develop a high-performance learning framework capable o...

To address the challenge of extracting multi-scale features from distribution line insulators in complex inspection environments—where varying scales and background interference complicate detection—this study propos...

Abstract Background Collagenous colitis (CC) is diagnosed histologically and is characterised by a thickened subepithelial collagen band together with inflammatory and epithelial changes. Although routine haematoxylin an...

As a key element of human settlements and fundamental features in maps, buildings play a critical role in urban planning and environmental monitoring. Automatically extracting buildings from remote sensing images is of s...

Reliable trajectory similarity estimation underpins applications such as map matching, mobility anomaly detection, and travel behavior analysis. However, traditional distance-based methods are computationally expensive a...

To address the sensitivity of traditional Two-Dimensional Principal Component Analysis (2DPCA) to outliers and the breakdown of variance-reconstruction equivalence under noise, we propose an Angle-Aware Weighted 2DPCA (A...

Abstract Understanding human emotions across multiple modalities such as text and images, is increasingly important for applications including content personalization, social media analysis, and Human–Computer Interact...

Abstract A prompt and precise diagnosis is necessary to lessen the worldwide burden of asthma, a common chronic respiratory condition. Spirometry is one of the resource-intensive conventional methods that frequently misc...

Intelligent mining area detection is fundamental for ecological monitoring and sustainable development of mining areas. However, current remote sensing detection lacks high-quality multimineral rotated object detection d...

Processing residues from adult Tenebrio molitor were evaluated as a sustainable source of chitin and chitosan through an optimized enzyme-assisted extraction strategy. Preliminary proximate analysis revealed a high chiti...

Abstract Early small fires in coal mines are of critical importance for mine safety, as most incidents begin as small fire sources. These fires essentially constitute a task of small-object detection. Detecting such targ...

Goal: Analysis of the glottal area during vocal fold vibration has gained increasing attention. However, traditional analysis requires manual, frame-by-frame glottal area annotation to compute the glottal area waveform, ...

Flood disasters, with high suddenness, wide impact and severe consequences, severely threaten ecological security, human lives, property and socioeconomic development. Optical remote sensing, though advantageous in spati...

Abstract The article presents a novel audio zero-watermarking technique that is free of creating any watermark data in the original audio. The strategy depends on the robust features of the audio in order to generate an ...

ABSTRACT With the advancement of satellite remote sensing technology, object detection based on high‐resolution remote sensing imagery has emerged as a prominent research focus in the field of computer vision. Although...

Unmanned Aerial Vehicles (UAVs) have become a prevalent tool for aerial image analysis, thanks to their agility in low-altitude flight and real-time sensing. However, objects in UAV imagery typically occupy minimal pixel...

Abstract The current work on emotion recognition considering EEG signals has attracted significant attention due to its advantages in fields like mental health, neural computing, and human-computer interaction. Nonethele...

Abstract Brain-computer interfaces (BCIs) were initially created to help individuals with disabilities control devices and communicate without muscle movement. Today, BCIs are used for prosthetic control, cognitive enhan...

Abstract Background Rapid and accurate pest diagnosis is essential for reducing crop losses and improving agricultural productivity. Most existing methods rely on deep learning-based object detection to classify pests in...

Zernike moments are well-suited for unmanned aerial vehicle scene matching because of their rotation invariance and robustness to noise. However, their high computational complexity poses challenges for meeting the real-...

Abstract Long-range dependency processing is the core challenge of sequence modeling, and traditional sequence modeling algorithms suffer from information decay and low parallel computing efficiency in ultra long sequenc...

The detection of transmission towers in remote sensing images presents significant challenges due to insufficient feature representation and significant object size variations, particularly at low spatial resolutions whe...

Unmanned aerial vehicle (UAV) aerial photography technology is crucial in various fields, including daily life, production, and security. However, it faces challenges in small object detection, such as extremely small ob...

Skin lesion segmentation poses a challenging problem in medical image analysis, with segmentation performance being highly sensitive to blurred boundaries, noise interference, and morphological diversity. To address thes...