Results 111 to 120 of about 26,718 (222)

Textile and colour defect detection using deep learning methods

Coloration Technology, EarlyView.
Abstract Recent advances in deep learning (DL) have significantly enhanced the detection of textile and colour defects. This review focuses specifically on the application of DL‐based methods for defect detection in textile and coloration processes, with an emphasis on object detection and related computer vision (CV) tasks.
Hao Cui, Abdel‐Fattah Seyam, Renzo Shamey   +2 more
wiley   +1 more source

SAAM: Stealthy Adversarial Attack on Monocular Depth Estimation

IEEE Access
Monocular depth estimation (MDE) is an important task in scene understanding, and significant improvements in its performance have been witnessed with the utilization of convolutional neural networks (CNNs).
Amira Guesmi, Muhammad Abdullah Hanif, Bassem Ouni, Muhammad Shafique   +3 more
doaj   +1 more source

Leveraging modified ex situ tomography data for segmentation of in situ synchrotron X‐ray computed tomography

Journal of Microscopy, EarlyView.
Abstract In situ synchrotron X‐ray computed tomography enables dynamic material studies. However, automated segmentation remains challenging due to complex imaging artefacts – like ring and cupping effects – and limited training data. We present a methodology for deep learning‐based segmentation by transforming high‐quality ex situ laboratory data to ...
Tristan Manchester, Adam Anders, Julio Spadotto, Hannah Eccleston, William Beavan, Hugues Arcis, Brian J. Connolly   +6 more
wiley   +1 more source

Searching for safety: Working conditions and policing in a US emergency department

Medical Anthropology Quarterly, EarlyView.
Abstract In the United States, emergency departments aren't supposed to turn anyone away. They are the safety‐net of the safety‐net providing life‐saving care. Yet, what happens to healthcare when conditions are so strained that patients and staff lash out at each other? What happens when the safety net becomes a carceral net?
Fabián Luis C. Fernández
wiley   +1 more source

Adversarial Patch for 3D Local Feature Extractor

CoRR
Local feature extractors are the cornerstone of many computer vision tasks. However, their vulnerability to adversarial attacks can significantly compromise their effectiveness. This paper discusses approaches to attack sophisticated local feature extraction algorithms and models to achieve two distinct goals: (1) forcing a match between originally non-
Yu Wen Pao, Li-Chang Lai, Hong-Yi Lin
openaire   +2 more sources

Powerful representation of the poor? German welfare associations' narrative advocacy during COVID‐19

Policy Studies Journal, EarlyView.
Abstract The COVID‐19 pandemic sparked unprecedented experimentation in the German social assistance system, leading to changes previously considered impracticable by policymakers. This included a sanctions moratorium, easier access to benefits, and temporary cash transfers, all of which were advocated by welfare associations—key organized interests ...
Christopher Smith Ochoa
wiley   +1 more source

A Survey for Deep Reinforcement Learning Based Network Intrusion Detection

Applied AI Letters, Volume 7, Issue 2, June 2026.
This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang, Alberto Acuto, Yihang Zhou, Dominik Wojtczak   +3 more
wiley   +1 more source

An Exploration of the Perceptions of Parents of Autistic Children and Young People About Counselling for Their Own Well‐Being: A Reflexive Thematic Analysis

Counselling and Psychotherapy Research, Volume 26, Issue 2, June 2026.
ABSTRACT Background Parents of autistic children and young people have higher levels of anxiety, depression, stress and burnout, PTSD, suicidality and lower quality of life. Current research focuses on interventions with outcomes directed at the child including parent training and psychoeducation.
Lisa Simpson, Rachel Casper‐White
wiley   +1 more source

A Z‐Score Template Method for Person‐Specific Augmentation of Clinical Brain MRI: An Investigation in Multiple Sclerosis

NMR in Biomedicine, Volume 39, Issue 6, June 2026.
This study develops a new Z‐score template method for person‐specific image synthesis to handle missing sequence problems as seen in multiple sclerosis (MS). The synthesized images show equivalency to source and cycle‐generative adversarial network (CycleGAN) outputs in both quality and treatment prediction in MS.
Olayinka Oladosu, Rehman Tariq, Shayan Shahrokhi, Yunyan Zhang   +3 more
wiley   +1 more source

OD-SHIELD: Convolutional Autoencoder-Based Defense Against Adversarial Patch Attacks in Object Detection

IEEE Access
In the evolving landscape of deep neural network security, adversarial patch attacks present a serious challenge for object detection systems. We introduce OD-Shield, a novel defense approach that employs a convolutional autoencoder framework to detect ...
Byeongchan Kim, Heemin Kim, Minjung Kang, Hyunjee Nam, Sunghwan Park, Jaewoo Lee, Il-Youp Kwak   +6 more
doaj   +1 more source