Results 241 to 250 of about 3,872,264 (315)

Enhancing wildlife monitoring with computer vision: A dataset for automated detection of barbary macaques. [PDF]

Data Brief
Qitout K, Lochin C, Desquesnes X, Maille A, Emile B.   +4 more
europepmc   +1 more source

In Situ Photopolymerization of Smectic B Liquid‐Crystalline Electrolytes from Mesogenic Phosphate–Diacrylate/Ionic Liquid Complexes for High‐Performance Soft Ionic Actuators

Advanced Robotics Research, EarlyView.
A flexible liquid‐crystalline electrolyte membrane via in situ photopolymerization of a phosphate‐functionalized mesogen, ionic liquid, and diacrylate monomer is developed. The resulting smectic B (SmB)‐phase structure enables 2D ion transport with high conductivity (10−4 S cm−1).
Chengyang Liu, Masafumi Yoshio
wiley   +1 more source

3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends

Advanced Robotics Research, EarlyView.
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu, Bin Cui, Xumin Huang, Xiaoyu (Rayne) Zheng, T. Thang Vo‐Doan, Ruirui Qiao   +5 more
wiley   +1 more source

From manual counting to YOLO: Using computer vision to automate large-scale fecundity assays in C. elegans. [PDF]

PLoS One
Peng L, Shui H, Janisch AN, Hesse SD, Feist VK, Gibson AK.   +5 more
europepmc   +1 more source

A Review on Sensor Technologies, Control Approaches, and Emerging Challenges in Soft Robotics

Advanced Robotics Research, EarlyView.
This review provides an introspective of sensors and controllers in soft robotics. Initially describing the current sensing methods, then moving on to the control methods utilized, and finally ending with challenges and future directions in soft robotics focusing on the material innovations, sensor fusion, and embedded intelligence for sensors and ...
Ean Lovett, Maxwell Hammond, Niloufar Seyfi, Amirreza Fahim Golestaneh, Venanzio Cichella, Caterina Lamuta   +5 more
wiley   +1 more source

Extrapolating rock physicochemical properties from discrete sample data using computer vision. [PDF]

PNAS Nexus
Grant LJC, Lington J, Carter EJ, Teagle DAH, Belgrano TM, Coggon RM.   +5 more
europepmc   +1 more source

Computer Vision-Based Techniques for Conveyor Belt Condition Monitoring: A Systematic Review. [PDF]

Sensors (Basel)
Rios-Colque P, Rios-Colque V, Rios-Colque L, Robles PA.   +3 more
europepmc   +1 more source

Assessing body composition via a smartphone computer vision application: High repeatability but method-dependent agreement compared with BODPOD and Inbody. [PDF]

PLOS Digit Health
Sisohor J, Ambegaonkar JP, Lindsey B, Wei Q, Shaul Y, Martin J.   +5 more
europepmc   +1 more source

Objective Assessment of Medication Adherence Through Automated Pill Detection Using a Computer Vision Framework: Development and Evaluation Study. [PDF]

JMIR AI
Liu H, Zheng Y, Wu B, Gan Y.
europepmc   +1 more source