Results 41 to 50 of about 10,967 (196)

Hard‐Magnetic Soft Millirobots in Underactuated Systems

open access: yesAdvanced 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   +4 more
wiley   +1 more source

A lightweight insulator defect detection algorithm based on the improved YOLOv5

open access: yesZhejiang dianli, 2023
Unmanned aerial vehicle (UAV) inspections now have emerged as a predominant approach for the examination of transmission lines, with a pivotal focus on the detection of insulator defects.
JI Shichao   +6 more
doaj   +1 more source

Real-time self-adaptive deep stereo

open access: yes, 2019
Deep convolutional neural networks trained end-to-end are the state-of-the-art methods to regress dense disparity maps from stereo pairs. These models, however, suffer from a notable decrease in accuracy when exposed to scenarios significantly different ...
Di Stefano, Luigi   +4 more
core   +1 more source

CRP Deficiency Rescues Periodontitis‐Induced Hippocampal Neurogenesis Impairment by Suppressing OPC‐Derived BMP4 Signaling in Rats

open access: yesAdvanced Science, EarlyView.
Chronic periodontitis elevates circulating CRP, which enters the hippocampus to upregulate BMP4 in oligodendrocyte precursor cells (OPCs), thereby impairing neurogenesis and inducing anxiety/depression‐like behaviors in rats. Counteracting this pathway, CRP deficiency helps confer functional resilience to OPCs.
Lingjie Li   +9 more
wiley   +1 more source

Self-Adaptive Hierarchical Sentence Model [PDF]

open access: yes, 2015
The ability to accurately model a sentence at varying stages (e.g., word-phrase-sentence) plays a central role in natural language processing. As an effort towards this goal we propose a self-adaptive hierarchical sentence model (AdaSent).
Lu, Zhengdong   +2 more
core  

vEMRec: High‐Resolution Volume Electron Microscopy Reconstruction Based on Structure‐Preserving and High‐Fidelity 3D Alignment

open access: yesAdvanced Science, EarlyView.
vEMRec is a frequency‐adaptive computational framework for three‐dimensional alignment in volume electron microscopy. It integrates feature‐based rigid alignment with Gaussian filter‐guided elastic registration to correct rigid misalignments and nonlinear distortions while preserving structural fidelity.
Zhenbang Zhang   +7 more
wiley   +1 more source

Microglial GPR35 Ameliorates Epileptogenesis and Neuroinflammation via PDGFA Domain 2 Signaling

open access: yesAdvanced Science, EarlyView.
Activation of microglial G protein–coupled receptor 35 (GPR35) by L‐kynurenic acid (L‐Kyna) initiates a platelet‐derived growth factor A (PDGFA)–dependent phosphoinositide 3‐kinase–protein kinase B (PI3K–AKT) signaling cascade that dampens hippocampal neuroinflammation, thereby restraining epileptogenesis, lowering seizure susceptibility, and ...
Qi Wang   +17 more
wiley   +1 more source

Coherent Online Video Style Transfer

open access: yes, 2017
Training a feed-forward network for fast neural style transfer of images is proven to be successful. However, the naive extension to process video frame by frame is prone to producing flickering results. We propose the first end-to-end network for online
Chen, Dongdong   +4 more
core   +1 more source

RT‐DETR‐DA for Complex Scenes: Distracted Driving Detection With Feature Interaction and Dynamic Perception

open access: yesAdvanced Intelligent Systems, EarlyView.
This work proposes RT‐DETR‐DA, an enhanced real‐time detection framework for identifying distracted driving in complex, real‐world environments. The model introduces a dynamic sparse gating multiscale attention module and an attention‐guided dual‐path fusion module to strengthen multiscale perception and cross‐layer feature interaction.
Yi Liu   +4 more
wiley   +1 more source

Regularizing Deep Networks by Modeling and Predicting Label Structure

open access: yes, 2018
We construct custom regularization functions for use in supervised training of deep neural networks. Our technique is applicable when the ground-truth labels themselves exhibit internal structure; we derive a regularizer by learning an autoencoder over ...
Maire, Michael   +2 more
core   +1 more source

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