Results 101 to 110 of about 449,358 (260)
Deep Learning as Applied in SAR Target Recognition and Terrain Classification
Deep learning such as deep neural networks has revolutionized the computer vision area. Deep learning-based algorithms have surpassed conventional algorithms in terms of performance by a significant margin. This paper reviews our works in the application
Xu Feng, Wang Haipeng, Jin Yaqiu
doaj +1 more source
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
Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models
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 +2 more
wiley +1 more source
Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling
A simulation‐driven framework for autonomous bulldozer leveling is presented, combining high‐fidelity terramechanics simulation with a neural‐network‐based reduced‐order model. Gradient‐based optimization enables efficient, low‐level blade control that balances leveling quality and operation time.
Harry Zhang +5 more
wiley +1 more source
Cross‐Scale Hierarchical Targeted Delivery System Based on Small‐Scale Magnetic Robots
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
We introduce AutomataGPT, a generative pretrained transformer (GPT) trained on synthetic spatiotemporal data from 2D cellular automata to learn symbolic rules. Demonstrating strong performance on both forward and inverse tasks, AutomataGPT establishes a scalable, domain‐agnostic framework for interpretable modeling, paving the way for future ...
Jaime A. Berkovich +2 more
wiley +1 more source
Discovery of H2 Receptor Antagonists as Colistin Enhancers by Targeting Acid Stress Response
This study identifies YqgB as a key target for restoring colistin susceptibility in mcr‐positive pathogens under acidic conditions by remodeling phospholipid composition and reducing LPS modification. Deep learning‐based screening reveals H2 receptor antagonists as novel colistin adjuvants. Further investigations indicate that ranitidine and famotidine
Jinju Cai +7 more
wiley +1 more source
De Novo Multi‐Mechanism Antimicrobial Peptide Design via Multimodal Deep Learning
Current AI‐driven peptide discovery often overlooks complex structural data. This study presents M3‐CAD, a generative pipeline that leverages 3D voxel coloring and a massive database of over 12 000 peptides to capture nuanced physicochemical contexts.
Xiaojuan Li +23 more
wiley +1 more source
Unveil Fundamental Graph Properties for Neural Architecture Search
This paper proposes NASGraph, a graph‐based framework that represents neural architectures as graphs whose structural properties determine performance. By revealing structure–performance relationships, NASGraph enables efficient neural architecture search with significantly reduced computation.
Zhenhan Huang +4 more
wiley +1 more source
Deep Learning‐Powered Scalable Cancer Organ Chip for Cancer Precision Medicine
This scalable, low‐cost Organ Chip platform, made via injection molding, uses capillary pinning for hydrogel confinement and supports versatile tissue coculture and robust imaging. Deep learning enables label‐free, sensitive phenotypic analysis.
Yu‐Chieh Yuan +24 more
wiley +1 more source

