Precision Autofocus in Optical Microscopy with Liquid Lenses Controlled by Deep Reinforcement Learning

Physics, Optics, Engineering, Mechanical Engineering, Electrical Engineering, Information Science, Computer Science, Artificial Intelligence,
microscopy   autofocus   liquid lens   deep reinforcement learning   optical system  

Precision Autofocus in Optical Microscopy with Liquid Lenses Controlled by Deep Reinforcement Learning Academic Background Microscopic imaging plays a crucial role in scientific research, biomedical studies, and engineering applications. However, traditional microscopes and autofocus techniques face hardware limitations and slow software speeds in ...

Parallel Mechanical Computing: Metamaterials That Can Multitask

Materials Science, Information Science, Computer Science,
parallel computing   metamaterials   mechanical computing   frequency multiplexing   wave-based computing  

Parallel Mechanical Computing: Metamaterials That Can Multitask Academic Background Decades after being replaced by digital computing platforms, analog computing has regained significant interest due to advancements in metamaterials and intricate fabrication techniques. Particularly, wave-based analog computers, which perform spatial transformation...

Basis Restricted Elastic Shape Analysis Framework for Surfaces

Mathematics, Physics, Mechanics, Information Science, Computer Science, Artificial Intelligence,
Elastic Shape Analysis   Surface Meshes   Geometric Deep Learning   Riemannian Shape Metrics   Human Body Analysis   Shape Registration   Random Shape Generation  

# Basis Restricted Elastic Shape Analysis on the Space of Unregistered Surfaces ## Introduction Analyzing three-dimensional (3D) surfaces has become increasingly important in computer vision, driven by the emergence of high-accuracy 3D scanning devices. These devices have significantly increased the availability of 3D data, enabling applications in...

Improving 3D Finger Traits Recognition via Generalizable Neural Rendering

Engineering, Electrical Engineering, Materials Science, Information Science, Electronic Information, Computer Science, Artificial Intelligence, Life Sciences, Bioengineering,
3D fingerprint recognition   neural rendering   finger biometrics   3D biometric traits   multi-modal biometrics  

Summary of FingerNeRF-Based 3D Finger Biometrics Research Report Background and Research Significance With the advancement of biometric technologies, three-dimensional (3D) biometrics have become a promising research direction due to their higher accuracy, robust anti-spoofing capabilities, and resistance to variations in capture angles. Among thes...

A Memory-Assisted Knowledge Transferring Framework with Curriculum Anticipation for Weakly Supervised Online Activity Detection

Engineering, Electrical Engineering, Information Science, Electronic Information, Computer Science, Artificial Intelligence,
weakly supervised learning   online activity detection   knowledge distillation   memory networks   curriculum learning  

Research Background and Significance In recent years, weakly supervised online activity detection (WS-OAD), as an important topic in high-level video understanding, has garnered widespread attention. Its primary goal is to detect ongoing activities frame-by-frame in streaming videos using only inexpensive video-level annotations. This task holds si...

Dynamic Attention Vision-Language Transformer Network for Person Re-Identification

Information Science, Electronic Information, Computer Science, Automation, Artificial Intelligence,
dynamic attention   vision-language   person re-identification   feature integration   deep learning   multimodal   domain adaptation  

Dynamic Attention Vision-Language Transformer Network for Person Re-Identification Research Report In recent years, multimodal person re-identification (ReID) has gained increasing attention in the field of computer vision. Person ReID aims to identify specific individuals across different camera views, serving as a critical technology in security ...

Sample Correlation for Fingerprinting Deep Face Recognition

Information Science, Computer Science, Automation, Artificial Intelligence,
sample correlation   deep face recognition   model fingerprinting   model stealing attacks   JPEG compression   intellectual property protection   knowledge distillation  

Report on Academic Paper: “Sample Correlation for Fingerprinting Deep Face Recognition” Background and Research Problem In recent years, the rapid advancements in deep learning technologies have significantly propelled the development of face recognition. However, commercial face recognition models face increasing intellectual property (IP) threats...

A Displacement Uncertainty-Based Method for Multi-Object Tracking in Low-Frame-Rate Videos

Engineering, Electrical Engineering, Information Science, Computer Science, Automation, Artificial Intelligence,
multi-object tracking   low-frame-rate videos   occlusion handling   uncertainty   optical flow   online tracking   Bayesian deep learning  

The Academic Report on Low-Frame-Rate Multi-Object Tracking Introduction and Research Background In recent years, multi-object tracking (MOT) has been widely applied in intelligent video surveillance, autonomous driving, and robotics vision. However, traditional MOT methods are predominantly designed for high-frame-rate videos and face significant ...

Anti-Fake Vaccine: Safeguarding Privacy Against Face Swapping via Visual-Semantic Dual Degradation

Information Science, Computer Science, Artificial Intelligence,
privacy protection   face swapping   adversarial perturbation   deepfake   visual degradation   semantic degradation  

Deepfake and Facial Privacy Protection: Innovative Research on Anti-Fake Vaccine Background and Motivation In recent years, advancements in deepfake technology have posed severe threats to personal privacy and social security. Facial swapping, a typical application of deepfake technology, is widely used in filmmaking and computer games, but its ris...

Weakly Supervised Semantic Segmentation of Driving Scenes Based on Few Annotated Pixels and Point Clouds

Engineering, Transportation Engineering, Information Science, Computer Science,
weakly supervised   semantic segmentation   driving scenes   point cloud data   pseudo labels  

Few Annotated Pixels and Point Cloud Based Weakly Supervised Semantic Segmentation of Driving Scenes Background and Research Issues Semantic segmentation, a critical task in computer vision, has extensive applications in domains like autonomous driving. However, traditional fully-supervised semantic segmentation methods require exhaustive pixel-lev...