Academic Background With the increasing complexity of artificial intelligence (AI) models and the growing demand for data privacy protection, Federated Learning (FL) has emerged as a hot research topic as a distributed machine learning paradigm. Federated Learning allows multiple clients to collaboratively train a global model without sharing local...

Research on Graph-Level Anomaly Detection Based on Dual-View Graph-of-Graph Representation Learning Academic Background In today’s data-driven world, graphs, as a powerful data structure, are widely used in fields such as social network analysis, financial fraud detection, and bioinformatics. Graphs can effectively represent complex relational data...

Continual Learning of Conjugated Visual Representations through Higher-Order Motion Flows: A Study on the CMOSFET Model Academic Background In the fields of artificial intelligence and computer vision, continual learning from continuous visual data streams has long been a challenge. Traditional machine learning methods typically rely on the assumpt...

Exploiting Instance-Label Dynamics through Reciprocal Anchored Contrastive Learning for Few-Shot Relation Extraction Academic Background In the field of Natural Language Processing (NLP), Relation Extraction (RE) is a fundamental task aimed at identifying and extracting relationships between entities in text. However, traditional supervised learnin...

Research on Efficient Fine-Grained 3D Scene Editing Based on Rotation-Invariant Neural Point Fields Academic Background In the fields of computer vision and graphics, modeling and rendering novel views of real scenes from multi-view images is a central problem. Neural Radiance Fields (NeRF) have recently demonstrated significant potential in genera...

Academic Background In today’s complex network systems, state estimation is a critical issue, especially when dealing with uncertainties and noise. Complex networks typically consist of multiple interconnected nodes, and the dynamic behavior of each node may be influenced by nonlinear factors. The Takagi-Sugeno (T-S) fuzzy model has demonstrated si...

Research on Flexible Gait Sensors for Quadruped Robot Applications Background Introduction With the widespread application of robots in daily life and industrial production, especially in scenarios requiring standardized, persistent, and heavy-duty operations, the development of intelligent robots has gradually become a trend. However, robots still...

As the global aging problem intensifies, the incidence of neurodegenerative diseases (such as Alzheimer’s Disease, AD) is increasing year by year. Brain aging (Brain Aging, BA) is one of the significant risk factors for neurodegenerative diseases, but it does not completely align with chronological age (Chronological Age, CA). Traditional methods f...

Sense of Presence in Virtual Reality: Exploration and Validation of Neurophysiological Markers Background Introduction In recent years, Virtual Reality (VR) technology has been widely applied in fields such as medicine, training, and rehabilitation. The core of VR lies in the user’s “sense of presence,” which refers to the immersive experience of “...

Multi-Material Decomposition Research Based on Spectral Diffusion Posterior Sampling Background Introduction In the field of medical imaging, CT (Computed Tomography) technology is widely used in disease diagnosis and treatment planning. In recent years, spectral CT has become a research hotspot due to its ability to provide energy-dependent attenu...