Results 141 to 150 of about 16,769 (297)

Visibility Estimation Based on Weakly Supervised Learning under Discrete Label Distribution. [PDF]

Sensors (Basel), 2023
Yan Q, Sun T, Zhang J, Xun L.
europepmc   +1 more source

Soft Robotic Excretory Care Simulator for Nursing Education: Functional and Perceptual Biomimetics Approach

Advanced Robotics Research, EarlyView.
A soft robotic simulator is developed to replicate the digital removal of feces (DRF), a sensitive yet essential nursing procedure. Integrating soft actuators, sensors, and a realistic rectal model, the simulator balances functional fidelity with perceptual realism. Engineering evaluations and nurse feedback confirm its potential to enhance training in
Shoko Miyagawa, Sota Suzuki, Shizuka Watanabe, Zebing Mao, Young Ah Seong, Toshinori Fujie, Tatsuhiro Horii, Kenjiro Tadakuma, Koichi Suzumori, Hiroyuki Nabae, Shingo Maeda   +10 more
wiley   +1 more source

Weakly Supervised Adversarial Training for Remote Sensing Image Cloud and Snow Detection

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Cloud and snow detection in remote sensing images has advanced significantly with the aid of deep learning methods. However, deep learning methods necessitate a large quantity of labeled data, which consumes a substantial amount of human and material ...
Jiajun Yang, Wenyuan Li, Keyan Chen, Zili Liu, Zhenwei Shi, Zhengxia Zou   +5 more
doaj   +1 more source

Hard‐Magnetic Soft Millirobots in Underactuated Systems

Advanced Robotics Research, EarlyView.
This review provides a comprehensive overview of hard‐magnetic soft millirobots in underactuated systems. It examines key advances in structural design, physics‐informed modeling, and control strategies, while highlighting the interplay among these domains.
Qiong Wang, Zixuan Zhang, Bingyan Li, Junkai Wang, Hongcheng Gu   +4 more
wiley   +1 more source

A method for spatial interpretation of weakly supervised deep learning models in computational pathology

Scientific Reports
Deep learning enables the modelling of high-resolution histopathology whole-slide images (WSI). Weakly supervised learning of tile-level data is typically applied for tasks where labels only exist on the patient or WSI level (e.g.
Abhinav Sharma, Bojing Liu, Mattias Rantalainen   +2 more
doaj   +1 more source

DDeep3M+: adaptive enhancement powered weakly supervised learning for neuron segmentation. [PDF]

Neurophotonics, 2023
Xiao R, Zhu L, Liao J, Wu X, Gong H, Huang J, Li P, Sheng B, Chen S.   +8 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

Weakly Supervised Learning by a Confusion Matrix of Contexts [PDF]

, 2019
Context consideration can help provide more background and related information for weakly supervised learning. The inclusion of less documented historical and environmental context in researching diabetes amongst Pima Indians uncovered reasons which were more likely to explain why some Pima Indians had much higher rates of diabetes than Caucasians ...
openaire   +1 more source

LLM‐Integrated Human–Robot Interaction System for Microrobots

Advanced Robotics Research, EarlyView.
This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley   +1 more source

P3CL: Pseudo-Label Confidence-Calibrated Curriculum Learning for Weakly Supervised Urban Airborne Laser Scanning Point Cloud Classification

Remote Sensing
Urban airborne laser scanning (ALS) point clouds cover extensive geographical areas, rendering dense point-level annotation economically prohibitive and limiting the feasibility of fully supervised learning.
Ziwei Luo, Tao Zeng, Jun Jiang, Ziyang Cai, Wanru Wu, Zhong Xie, Yongyang Xu   +6 more
doaj   +1 more source