Results 81 to 90 of about 32,830 (265)
Side information-driven image coding for hybrid machine–human vision
With the development of machine learning, advanced photography and image transmission systems, images are being processed more and more by machines, so image coding for machines (ICM) came into being.
Zhongpeng Zhang +2 more
doaj +1 more source
Cross‐Modal Denoising and Integration of Spatial Multi‐Omics Data with CANDIES
In this paper, we introduce CANDIES, which leverages a conditional diffusion model and contrastive learning to effectively denoise and integrate spatial multi‐omics data. We conduct extensive evaluations on diverse synthetic and real datasets, CANDIES shows superior performance on various downstream tasks, including denoising, spatial domain ...
Ye Liu +5 more
wiley +1 more source
We investigate whether Montessori and traditional schooling systems shape the developmental trajectory of large‐scale brain dynamics in different ways. We quantify the arrow of time (“non‐reversibility”) in neural activity during resting state and movie‐watching, revealing distinct maturational patterns.
Elvira del Agua +6 more
wiley +1 more source
A multilevel segmentation method of asymmetric semantics based on deep learning
An asymmetric semantic multi‐level segmentation method based on depth learning is proposed in order to improve the precision and effect of semantic segmentation.
Angxin Liu, Yongbiao Yang
doaj +1 more source
Decoding Spatial Heterogeneity and Multi‐Omics Regulation with Hierarchical Graph Learning
ABSTRACT Recent advances in spatial multi‐omics technologies have enabled the simultaneous profiling of multiple molecular layers within the same tissue slice, providing unprecedented opportunities to investigate tissue spatial organization. However, most existing computational methods identify spatial domains in a purely data‐driven manner, rarely ...
Jiazhou Chen +6 more
wiley +1 more source
Explainable AI (XAI) in image segmentation in medicine, industry, and beyond: A survey
Explainable AI (XAI) has found numerous applications in computer vision. While image classification-based explainability techniques have garnered significant attention, their counterparts in semantic segmentation have been relatively neglected. Given the
Rokas Gipiškis +2 more
doaj +1 more source
MarginPath is a novel vision‐language system that automates breast cancer margin assessment using a single label‐free multiphoton microscopy image. By integrating tumor‐associated collagen signatures with virtual H&E imaging, it generates accurate margin heatmaps and comprehensive diagnostic reports.
Shu Wang +15 more
wiley +1 more source
Semantic segmentation of agricultural images: A survey
As an important research topic in recent years, semantic segmentation has been widely applied to image understanding problems in various fields. With the successful application of deep learning methods in machine vision, the superior performance has been
Zifei Luo +4 more
doaj +1 more source
From interactive to semantic image segmentation
This thesis investigates two well defined problems in image segmentation, viz. interactive and semantic image segmentation. Interactive segmentation involves power assisting a user in cutting out objects from an image, whereas semantic segmentation involves partitioning pixels in an image into object categories. We investigate various models and energy
openaire +2 more sources
A biomimetic artificial intelligence system, PancDS, has been developed to distinguish pancreatic ductal adenocarcinoma from mass‐forming pancreatitis by adaptively integrating clinical data, radiomics, and deep learning features. Validated across multicenter, reader‐study, and prospective settings, PancDS improves diagnostic accuracy, particularly for
Zhibo Wang +13 more
wiley +1 more source

