Low-dose computed tomography (LDCT) reduces radiation exposure but suffers from high noise, impacting image quality and diagnostic accuracy. Supervised learning has helped address this challenge but ...

Generative artificial intelligence (GAI) has emerged as a rapidly burgeoning field demonstrating significant potential in creating diverse content intelligently and automatically. To support such ...

With the development of e-commerce, the types of logistics services have become diverse. In response to the logistics requirements in urban environments, this paper introduces a logistics system that ...

This study presents a comprehensive survey on Quantum Machine Learning (QML) along with its current status, challenges, and perspectives. QML combines quantum computing and machine learning to solve ...

Hyperspectral images (HSIs) with high spatial resolution are challenging to obtain directly due to sensor limitations. Deep learning is able to provide an end-to-end reconstruction solution from low ...

Human gaze provides valuable information on human focus and intentions, making it a crucial area of research. Recently, deep learning has revolutionized appearance-based gaze estimation. However, due ...

This letter presents Switch-SLAM, switching-based LiDAR-inertial-visual SLAM for degenerate environments, designed to tackle the challenges in degenerate environments for LiDAR and visual SLAM. Switch ...

In this letter, we present SemGuarder, a novel deep learning-based semantic communication (DLSC) system that simultaneously incorporates physical-layer semantic encryption and adversarial ...

Semantic segmentation of high-resolution remote sensing images is vital in downstream applications such as land-cover mapping, urban planning, and disaster assessment. Existing Transformer-based ...

As Metaverse emerges as the next-generation Internet paradigm, the ability to efficiently generate content is paramount. AI-Generated Content (AIGC) emerges as a key solution, yet the ...

Self-driving vehicles are a maturing technology with the potential to reshape mobility by enhancing the safety, accessibility, efficiency, and convenience of automotive transportation. Safety-critical ...

The utilization of both constrained and unconstrained-based optimization for solving constrained multi-objective optimization problems (CMOPs) has become prevalent among recently proposed constrained ...