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The growing demand for intensive artificial intelligence applications, such as deep neural networks and Large Language Models (LLMs), has driven the creation of architecture extensions and accelerators for matrix multipl...

Generative artificial intelligence systems increasingly enable novice users to create complex websites with minimal technical expertise; however, these users often struggle to evaluate the visual quality of AI-generated ...

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-...

In classical vernacular Chinese fiction, inferring affective stance in the presence of rhetorical devices often depends on implicit semantics and contextual cues, which poses substantial challenges for joint pragmatic mo...

Foothold selection for hexapod robots in complex terrain presents a significant challenge, demanding both high computational efficiency and robust adaptability. To address this issue, this paper introduces a foothold sel...

Reliable beat-level arrhythmia detection from electrocardiogram (ECG) signals is essential for continuous patient monitoring. However, many existing deep learning models remain computationally expensive and are sensitive...

Agile, dynamic, and safe motion planning in interactive environments is a key challenge for autonomous vehicles. Most research has focused on enhancing established planning algorithms, often aiming to improve optimality ...

In the present study, the transmission error (TE) behaviour of an identical involute spur gear pair dynamically coupled with an attached subsystem is investigated through numerical modelling. The surrounding mechanical s...

Dairy farms increasingly deploy sensor networks that generate high-frequency behavioral and spatial data, yet translating these multimodal streams into actionable welfare insights remains a key challenge. This study pres...

Ising machines, including quantum annealing machines, are promising next-generation computers for combinatorial optimization problems. However, due to hardware limitations, most Ising-type hardware can only solve objecti...

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...

The remarkable success of large language models (LLMs) in code generation has transformed software development, with systems like Codex, CodeGen, and StarCoder demonstrating strong capabilities in synthesizing functional...

Camera rigs for Advanced Driver Assistance Systems (ADAS) are subject to design choices of each vehicle variant; therefore, ADAS algorithms should be rig-invariant or tunable with limited additional data. Recently, the A...

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...