Results 181 to 190 of about 181,778 (304)

Integrative Advances in Equine Genomics From Reference Assemblies to Evolutionary History and Key Traits. [PDF]

Evol Appl
Lu Y, Ma R, Wang B, Wu J, Chong Y, Gao Z, Deng W.   +6 more
europepmc   +1 more source

ChicGrasp: Imitation‐Learning‐Based Customized Dual‐Jaw Gripper Control for Manipulation of Delicate, Irregular Bio‐Products

Advanced Robotics Research, EarlyView.
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar, Zhengtong Xu, Siavash Mahmoudi, Pouya Sohrabipour, Chaitanya Pallerla, Yu She, Wan Shou, Philip Glen Crandall, Dongyi Wang   +8 more
wiley   +1 more source

A U-Net Improved Version for Crop and Weed Segmentation from Aerial Images. [PDF]

Sensors (Basel)
Bunica-Mihai A, Popescu D, Ichim L.
europepmc   +1 more source

Liquid Crystalline Elastomers in Soft Robotics: Assessing Promise and Limitations

Advanced Robotics Research, EarlyView.
Liquid crystalline elastomers (LCEs) are programmable soft materials that undergo large, anisotropic deformation in response to external stimuli. Their molecular alignment encodes directional actuation in a monolithic structure, making them long‐standing candidates for soft robotic systems.
Justin M. Speregen, Timothy J. White
wiley   +1 more source

Transferable Migration Framework Derived from a Large-scale Tertiary Hospital EHR System. [PDF]

Healthc Inform Res
Yu H, Lee K, Lee S, Kim Y.
europepmc   +1 more source

Robotic Control for Human–Robot Collaborative Assembly Based on Digital Human Model and Reinforcement Learning

Advanced Robotics Research, EarlyView.
This work presents a robotic control method for human–robot collaborative assembly based on a biomechanics‐constrained digital human model. Reinforcement learning is used to generate physiologically plausible human motion trajectories, which are integrated into a virtual environment for robot control learning.
Bitao Yao, Hongzhou Ai, Wenjun Xu, Zude Zhou, Lihui Wang   +4 more
wiley   +1 more source

OLD ARCHITECTURE OR MODERN ARCHITECTURE IN UZBEKISTAN

WIELOKIERUNKOWOSC JAKO GWARANCJA POSTĘPU NAUKOWEGO - TOM 1, 2020
Zoki Allahanov, Sohib Isakov
openaire   +2 more sources

ImageNet pre-training and two-step transfer learning in chromosome image classification. [PDF]

Sci Rep
Chen T, Xie C, Zhang W, Li Y, Ke W, Li T, Huang X, Li K.   +7 more
europepmc   +1 more source

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

Advanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source

Modernity and Modernities. Challenges for the Historiography of Modern Architecture

, 2015
sponsorship: Tongji ...
openaire   +1 more source