Results 81 to 90 of about 4,047,749 (292)
B-CNN: Branch Convolutional Neural Network for Hierarchical Classification
CoRR, 2017 9 pages, 8 ...
Xinqi Zhu, Michael Bain 0001
openaire +2 more sources
Cross‐Scale Hierarchical Targeted Delivery System Based on Small‐Scale Magnetic Robots
Advanced Robotics Research, EarlyView.This article reviews a cross‐scale hierarchical targeted delivery system that integrates magnetic continuum robots and magnetic microrobots. By combining rapid long‐range navigation with precise microscale targeting, the system overcomes key limitations of single‐scale approaches.
Junjian Zhou +4 more
wiley +1 more source
Advanced Robotics Research, EarlyView.This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source
Energy-Efficient Architecture for CNNs Inference on Heterogeneous FPGA
Journal of Low Power Electronics and Applications, 2019 Due to the huge requirements in terms of both computational and memory capabilities, implementing energy-efficient and high-performance Convolutional Neural Networks (CNNs) by exploiting embedded systems still represents a major challenge for hardware ...
Fanny Spagnolo +3 more
doaj +1 more source
Enhanced image-based malware classification using transformer-based convolutional neural networks (CNNs) [PDF]
As malware samples grow in complexity and employ advanced evasion techniques, traditional detection methods are insufficient for accurately classifying large volumes of sophisticated malware variants.
Ashawa, Moses; id_orcid +10 more
core +1 more source
Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges
Advanced Robotics Research, EarlyView.This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder +3 more
wiley +1 more source
3D Discrete Matrix-Product Operation and Its Generalization
Journal of Function SpacesTwo-dimensional (2D) discrete matrix-product operation (DMPO) and its corresponding matrix-product neural networks (MPNNs) are the substitutions of 2D discrete convolutional operation and its corresponding convolutional neural networks (CNNs ...
Chuanhui Shan, Hu Li, Chao Han
doaj +1 more source
Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network
Sensors, 2018 Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules.
Xiaofeng Du, Xiaobo Qu, Yifan He, Di Guo
doaj +1 more source
Flexible Sensors for Robotics Tactile Perception: A Review
Advanced Robotics Research, EarlyView.Flexible tactile sensing for robotics is reviewed through four interconnected dimensions. Physical mechanisms include piezoresistive, capacitive, piezoelectric, triboelectric, iontronic, and optical sensing. Structural design includes bioinspired, defect‐based, and MEMS‐based tactile systems.
Yu Song, Ying Chen, Yihao Chen, Xue Feng
wiley +1 more source
IEEE Access, 2019 convolutional neural networks (CNNs) in the frequency domain is of great significance for extending the deep learning principle to the frequency domain.
Jinhua Lin, Lin Ma, Yu Yao
doaj +1 more source