Results 151 to 160 of about 51,355 (218)
Crop pest image recognition based on the improved ViT method
Xueqian Fu +6 more
semanticscholar +1 more source
The use of deidentified organ donor testes for research
Abstract Our knowledge of testis development and function mainly comes from research using mammalian model organisms, primarily the mouse. However, there are integral differences between men and other mammalian species regarding cellular composition and expression profiles during fetal and post‐natal testis development and in the mature testis ...
Marina V. Pryzhkova +4 more
wiley +1 more source
«Différant des Autres», Espacements et Temporalités Spectrales
ABSTRACT That night that he agreed to our suggestion that we accompany him outside, for the whole night or until the overflow has passed, M seemed to be in direct contact with all the layers of astronomy, inhabiting all temporalities simultaneously. Outside, lying/sitting on the picnic table, in the pitch‐black darkness of the night in the woods, under
Amélie‐Anne Mailhot
wiley +1 more source
“Flames Over Persepolis”: New Scientific Evidence Supporting Historical Perspectives
ABSTRACT This study investigates the burning of Persepolis Terrace, historically attributed to Alexander III in 330 bce. A review of classical accounts and excavation reports, combined with diagnostic surveys, confirms the fire's historicity and provides novel insights.
Maria Letizia Amadori +10 more
wiley +1 more source
CTBViT: A novel ViT for tuberculosis classification with efficient block and randomized classifier
Si-Yuan Lu +4 more
semanticscholar +1 more source
Abstract Automated insect identification systems hold significant value for biodiversity monitoring, pest management, citizen science initiatives and systematic studies, particularly in an era of declining expertise in insect taxonomy. However, current deep learning approaches often rely on standardized specimen photos from limited‐angles and ...
Xinkai Wang +10 more
wiley +1 more source
Textile and colour defect detection using deep learning methods
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 +2 more
wiley +1 more source
Summary Background and Objectives Deep learning‐convolutional neural networks (DL‐CNNs) have demonstrated high diagnostic accuracy within the domain of dermoscopy. However, many clinical settings lack dermoscopic devices, requiring reliance on close‐up images. This study evaluates the robustness of a DL‐CNN trained on dermoscopic images when challenged
Anastasia Sophie Vollmer +6 more
wiley +1 more source

