Results 71 to 80 of about 177,128 (280)

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

UTact: Underwater Vision‐Based Tactile Sensor with Geometry Reconstruction and Contact Force Estimation

Advanced Robotics Research, EarlyView.
Embedded flexible sensing technologies advance underwater soft robotics, yet most systems still suffer from hysteresis and limited perceptiveness. Instead, vision‐based tactile sensors provide reliable and rapid feedback essential for complex underwater tasks.
Qiyi Zhang, Zonghao Zuo, Haoxuan Wang, Bin Liu, Yilidusi Yilihamu, Li Wen   +5 more
wiley   +1 more source

Fine Tuning Hyperparameters of Deep Learning Models Using Metaheuristic Accelerated Particle Swarm Optimization Algorithm

IEEE Access
In recent years, Convolutional Neural Networks (CNNs) have emerged as powerful tools for solving complex real-world problems, particularly in the domain of image processing.
Abdel-Hamid M. Emara, Ghada Atteia, Jawad Hasan Alkhateeb   +2 more
doaj   +1 more source

CNN+CNN: Convolutional Decoders for Image Captioning

, 2018
Image captioning is a challenging task that combines the field of computer vision and natural language processing. A variety of approaches have been proposed to achieve the goal of automatically describing an image, and recurrent neural network (RNN) or long-short term memory (LSTM) based models dominate this field.
Wang, Qingzhong, Chan, Antoni B.
openaire   +2 more sources

Improving the Robustness of Visual Teach‐and‐Repeat Navigation Using Drift Error Correction and Event‐Based Vision for Low‐Light Environments

Advanced Robotics Research, EarlyView.
Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley   +1 more source

Synthesis and modification strategies of g-C3N4 nanosheets for photocatalytic applications

Advanced Powder Materials
Graphitic carbon nitride nanosheets (CNNs) become the most promising member in the carbon nitride family benefitted from their two-dimensional structural features.
Long Chen, Michael A. Maigbay, Miao Li, Xiaoqing Qiu   +3 more
doaj   +1 more source

CNN

, 2016
Ted Turner launched Cable News Network (CNN), the world’s first twenty-four-hour news channel, in 1980. Broadcast network journalists and media pundits initially dismissed CNN as the “Chicken Noodle Network,” pointing to its poor production values and small audience share.
openaire   +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

An Extensive Study of Convolutional Neural Networks: Applications in Computer Vision for Improved Robotics Perceptions

Sensors
Convolutional neural networks (CNNs), a type of artificial neural network (ANN) in the deep learning (DL) domain, have gained popularity in several computer vision applications and are attracting research in other fields, including robotic perception ...
Ravi Raj, Andrzej Kos
doaj   +1 more source

Study on Representation Invariances of CNNs and Human Visual Information Processing Based on Data Augmentation

Brain Sciences, 2020
Representation invariance plays a significant role in the performance of deep convolutional neural networks (CNNs) and human visual information processing in various complicated image-based tasks.
Yibo Cui, Chi Zhang, Kai Qiao, Linyuan Wang, Bin Yan, Li Tong   +5 more
doaj   +1 more source