Rise-Editing: Rotation-Invariant Neural Point Fields with Interactive Segmentation for Fine-Grained and Efficient Editing

Rise-Editing: Rotation-Invariant Neural Point Fields with Interactive Segmentation for Fine-Grained and Efficient Editing

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...

Anxiety Disorder Identification with Biomarker Detection through Subspace-Enhanced Hypergraph Neural Network

Anxiety Disorder Identification with Biomarker Detection through Subspace-Enhanced Hypergraph Neural Network

Anxiety Disorder Identification and Biomarker Detection Based on Subspace-Enhanced Hypergraph Neural Network Academic Background Anxiety Disorders (ADs) are prevalent mental health issues globally, affecting approximately 7.3% of the population. Patients with anxiety disorders typically exhibit excessive fear, worry, and related behavioral abnormal...

Set-Membership Estimation for T–S Fuzzy Complex Networks: A Dynamic Coding-Decoding Mechanism

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...

Gait Sensors with Customized Protruding Structures for Quadruped Robot Applications

Gait Sensors with Customized Protruding Structures for Quadruped Robot Applications

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...

Evaluating Generalizability of Oncology Trial Results to Real-World Patients Using Machine Learning-Based Trial Emulations

Evaluation of the Generalizability of Oncology Trial Results Using Machine Learning-Based Trial Emulations Academic Background Randomized Controlled Trials (RCTs) are the gold standard for evaluating the efficacy of anti-cancer drugs, but their results often cannot be directly generalized to real-world oncology patients. RCTs typically employ stric...

Deep Learning to Quantify the Pace of Brain Aging in Relation to Neurocognitive Changes

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...