Multiscale Footprints Reveal the Organization of Cis-Regulatory Elements

Information Science, Artificial Intelligence, Life Sciences, Cell Biology, Biochemistry, Bioengineering, Genetics,
cis-regulatory elements   chromatin accessibility   transcription factors   deep learning   single-cell sequencing   genomics   cell differentiation  

Multiscale Footprints Reveal the Role of Cis-Regulatory Elements in Cell Differentiation and Aging Background Introduction The regulation of gene expression is a key mechanism in cell fate determination and disease development, and cis-regulatory elements (CREs) play a crucial role in this process. CREs dynamically regulate gene expression by bindi...

Artificial Intelligence and Terrestrial Point Clouds for Forest Monitoring

Engineering, Environmental Engineering, Information Science, Computer Science, Artificial Intelligence, Life Sciences, Botany,
deep learning   machine learning   forest inventory   tree characteristics   open data   precision forestry   lidar  

Artificial Intelligence and Terrestrial LiDAR Point Clouds in Forest Monitoring: Academic Report Academic Background With the increasing importance of global climate change and forest resource management, precision forestry has become a key direction in modern forest management. Precision forestry relies on high-precision forest data collection and...

Multimodal Deep Learning Improves Recurrence Risk Prediction in Pediatric Low-Grade Gliomas

Information Science, Artificial Intelligence, Medicine, Neurology, Medical Imaging, Oncology,
pediatric low-grade gliomas   deep learning   postoperative recurrence prediction   multimodal model   magnetic resonance imaging   risk stratification   survival analysis  

Application of Deep Learning in Postoperative Recurrence Prediction for Pediatric Low-Grade Gliomas Background Pediatric Low-Grade Gliomas (PLGGs) are one of the most common types of brain tumors in children, accounting for 30%-50% of all central nervous system tumors in children. Although the prognosis of PLGGs is relatively favorable, the risk of...

Learning Meshing from Delaunay Triangulation for 3D Shape Representation

Information Science, Computer Science, Artificial Intelligence,
Delaunay triangulation   graph neural network   point cloud   surface reconstruction   multi-label supervision   local graph iteration   high-precision reconstruction  

Learning Meshing from Delaunay Triangulation for 3D Shape Representation Academic Background Surface reconstruction from point clouds is a long-standing problem in computer vision and graphics. Traditional implicit methods, such as Poisson surface reconstruction, compute an implicit function and extract the surface using the Marching Cubes algorith...

LDTrack: Dynamic People Tracking by Service Robots Using Diffusion Models

Information Science, Computer Science, Artificial Intelligence,
robotic person tracking   service robots   diffusion models   intraclass variations   cluttered and crowded environments  

Dynamic People Tracking by Service Robots Using Diffusion Models Academic Background Tracking dynamic people in cluttered and crowded human-centered environments is a challenging problem in robotics. Due to intraclass variations such as occlusions, pose deformations, and lighting changes, traditional tracking methods often struggle to accurately id...

CANet:Context-Aware Multi-View Stereo Network for Efficient Edge-Preserving Depth Estimation

Information Science, Computer Science, Artificial Intelligence,
multi-view stereo   depth estimation   depth refinement   3D dense reconstruction   correspondence matching  

Academic Background and Problem Statement Multi-View Stereo (MVS) is a fundamental task in 3D computer vision that aims to recover the 3D geometry of a scene from multiple posed images. This technology has broad applications in robotics, scene understanding, augmented reality, and more. In recent years, learning-based MVS methods have achieved sign...