A5004645356- X-ray Diffraction in Crystallography
- Crystallization and Solubility Studies
- Radiomics and Machine Learning in Medical Imaging
- AI in cancer detection
- Network Security and Intrusion Detection
- CO2 Reduction Techniques and Catalysts
- Advanced Graph Neural Networks
- Advanced Neural Network Applications
- Semantic Web and Ontologies
- Anomaly Detection Techniques and Applications
- Topic Modeling
- Congenital Heart Disease Studies
- Medical Image Segmentation Techniques
- Advanced X-ray and CT Imaging
- Retinal Imaging and Analysis
- Moringa oleifera research and applications
- Carbon dioxide utilization in catalysis
- Metaheuristic Optimization Algorithms Research
- Cardiomyopathy and Myosin Studies
- Advanced battery technologies research
- Selenium in Biological Systems
- Internet Traffic Analysis and Secure E-voting
- Ionic liquids properties and applications
- Cardiovascular Function and Risk Factors
- Advanced Photocatalysis Techniques
Southern Medical University
2023-2024
Guangdong Provincial People's Hospital
2022-2024
Zhejiang Normal University
2023-2024
Jiangnan University
2024
Guangdong Academy of Medical Sciences
2022-2024
Peng Cheng Laboratory
2023-2024
Guangzhou University
2022
Fudan University
2022
Biomedical image segmentation plays a central role in quantitative analysis, clinical diagnosis, and medical intervention. In the light of fully convolutional networks (FCN) U-Net, deep (DNNs) have made significant contributions to biomedical applications. this paper, we propose three different multi-scale dense connections (MDC) for encoder, decoder U-shaped architectures, across them. Based on connections, densely connected U-Net (MDU-Net) segmentation. MDU-Net directly fuses neighboring...
Abstract Background Selenium is essential for livestock and human health. The traditional way of adding selenium to diets has limitations, there a growing trend provide with safe efficient source through selenium-enriched pasture. Therefore, this study was conducted investigate the effects enrichment on fermentation characteristics, content, morphology, microbial community in vitro digestion silage alfalfa by using unenriched (CK) (Se) as raw material silage. Results In study, significantly...
Abstract Returning CO 2 to liquid ethanol powered by clean energy offers considerable economic benefits and contributes reaching the goal of carbon neutrality, but it remains a formidable challenge achieve high selectivity due inevitable strong competition among various pathways. Herein, an investigation is presented accelerate electroreduction via preferentially stabilizing precarious watershed intermediates ( * CHCOH) creating adsorbate‐adsorbate interaction. The highly ordered CuOx...
Deep reinforcement learning (DRL) has shown promise in solving challenging combinatorial optimization (CO) problems, such as the traveling salesman problem (TSP) and vehicle routing (VRP). However, existing DRL methods rely on manually designed reward functions, which may be inaccurate or unrealistic. Moreover, traditional algorithms suffer from unstable training sparse problems. This paper proposes GIRL (Generative Inverse Reinforcement Learning), a method to learn 2-opt heuristics without...
Coronary artery disease (CAD) is the most common cause of death globally, and its diagnosis usually based on manual myocardial (MYO) segmentation MRI sequences. As tedious, time-consuming, with low replicability, automatic MYO using machine learning techniques has been widely explored recently. However, almost all existing methods treat input sequences independently, which fails to capture temporal information between sequences, e.g., shape location myocardium in along time. In this article,...
Large language models (LLMs), while exhibiting exceptional performance, suffer from hallucinations, especially on knowledge-intensive tasks. Existing works propose to augment LLMs with individual text units retrieved external knowledge corpora alleviate the issue. However, in many domains, texts are interconnected (e.g., academic papers a bibliographic graph linked by citations and co-authorships) which form (text-attributed) graph. The such graphs is encoded not only single texts/nodes but...
The recent emergence of diffusion models has significantly advanced the precision learnable priors, presenting innovative avenues for addressing inverse problems. Since problems inherently entail maximum a posteriori estimation, previous works have endeavored to integrate priors into optimization frameworks. However, prevailing optimization-based algorithms primarily exploit prior information within while neglecting their denoising capability. To bridge this gap, work leverages process...
Intrusion detection is a crucial aspect of modern cybersecurity, aimed at identifying and responding to potential security threats within computer systems, networks, applications. One the major challenges faced by intrusion systems accurate response attack traffic, which typically much lower compared normal traffic. This challenge becomes even more pronounced when traffic further classified into different categories, especially presents as long-tail distribution. To address these challenges,...