Background Introduction In the field of computer vision, research on visual attention models aims to simulate how the human visual system selects regions of interest from images or natural scenes. The human brain’s ability to quickly and accurately identify salient regions in visual scenes is of great significance in tasks such as image processing,...
Academic Background and Problem Introduction In the field of Multi-Expert Multi-Criteria Decision-Making (MEMCDM), effectively handling uncertainty and imprecise information has always been a core challenge. Particularly in complex scenarios involving multiple experts and decision criteria, experts’ opinions often diverge, complicating the decision...
Academic Background In recent years, Chinese word embeddings have attracted significant attention in the field of Natural Language Processing (NLP). Unlike English, the complex and diverse structure of Chinese characters presents unique challenges for semantic representation. Traditional word vector models, such as Word2Vec, often fail to fully cap...
Background Introduction In the field of machine learning, Semi-Supervised Learning (SSL) has garnered significant attention due to its ability to leverage a small amount of labeled data and a large amount of unlabeled data for learning. Particularly in scenarios where data labeling is costly, graph-based semi-supervised learning methods have become...
Academic Background In recent years, with the rapid development of large language models (LLMs), their applications in the field of natural language processing (NLP) have become increasingly widespread. LLMs such as ChatGPT and LLaMA have demonstrated powerful capabilities in language generation and comprehension, even excelling in emotional expres...
Academic Background In fields such as decision analysis, pattern recognition, and medical diagnosis, fuzzy set theory provides essential mathematical tools for handling uncertainty and ambiguity. Traditional fuzzy sets (Fuzzy Set, FS) and intuitionistic fuzzy sets (Intuitionistic Fuzzy Set, IFS) have certain limitations when dealing with complex da...
Academic Background In today’s healthcare environment, medical imaging plays a crucial role in disease diagnosis, treatment planning, and health management. However, traditional medical image analysis methods face numerous challenges, such as overfitting, high computational costs, limited generalization capabilities, and issues related to noise, si...
Background Introduction Dementia is a global health issue that significantly impacts patients’ quality of life and places a substantial burden on healthcare systems. Alzheimer’s Disease (AD) and Frontotemporal Dementia (FTD) are two common types of dementia, and their overlapping symptoms make accurate diagnosis and targeted treatment development p...
Background Introduction With the rapid development of unmanned aerial vehicle (UAV) technology, low-altitude remote sensing images captured by UAVs have been widely used in tasks such as disaster management, search and rescue. However, small object detection in UAV images remains a challenging problem. Due to the fact that small objects occupy only...
Academic Background With the continuous growth of global energy demand, Energy Storage Technology (EST) plays a crucial role in mitigating environmental impacts and reducing carbon footprints. EST is not only an essential component of renewable energy but also a key factor in decarbonizing the global energy structure. However, selecting the appropr...