Results 121 to 130 of about 12,040,618 (293)

Multiscale Circuit Architecture Associated With Memory Dysfunction in Temporal Lobe Epilepsy

Advanced Science, EarlyView.
A multiscale precision‐mapping framework reveals that memory impairment in temporal lobe epilepsy arises from the convergence of focal medial temporal pathology, strategic white matter disconnection, and limbic‐centered metabolic network dysfunction.
Jiajie Mo, Qiwen Yuan, Pengfei Zhang, Lin Sang, Zhong Zheng, Baotian Zhao, Xiu Wang, Chao Zhang, Wenhan Hu, Xiaoqiu Shao, Jianguo Zhang, Ruijin Yang, Kai Zhang   +12 more
wiley   +1 more source

Multiscale Spatial Fusion Feature‐Driven Characterization of Gastric Cancer Invasive Margins: A Multicenter Cohort Study for Preoperative Accurate Differentiation Between T4a and T4b Subtypes

Advanced Science, EarlyView.
This study develops a multi‐dimensional vision Transformer‐based model, GAVR, to accurately distinguish gastric cancer T4a/b stages preoperatively. Validated across multi‐center cohorts, it achieves excellent performance and significantly improves radiologists’ diagnostic accuracy, offering a promising tool for clinical decision‐making.
Guoliang Zheng, Xiaomiao Chai, Peng Jin, Xin Xin, Yingjie Li, Chun Yang, Jia Wei, Zishuo Yan, Jingyu Zhang, Qianning Zhao, Yingchen Han, Ning Zhang, Fuze Li, Bo Qiao, Huan Wang, Huachuan Zheng, Yan Li, Xin Zhang, Yan Zhao, Wenjun Mao, Jing Zhang   +20 more
wiley   +1 more source

Text-based Semantic Annotation Service for Multimedia Content in the Esperonto project [PDF]

, 2004
Within the Esperonto project, an integration of NLP, ontologies and other knowledge bases, is being performed with the goal to implement a semantic annotation service that upgrades the actual Web towards the emerging Semantic Web.
Corcho, Oscar, Contreras, Jesús, Crispi, C., Declerck, T.   +3 more
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Unified DeepLabV3+ for Semi-Dark Image Semantic Segmentation. [PDF]

Sensors (Basel), 2022
Memon MM, Hashmani MA, Junejo AZ, Rizvi SS, Raza K.   +4 more
europepmc   +1 more source

Image semantic segmentation of indoor scenes: A survey

Computer Vision and Image Understanding
This survey provides a comprehensive evaluation of various deep learning-based segmentation architectures. It covers a wide range of models, from traditional ones like FCN and PSPNet to more modern approaches like SegFormer and FAN. In addition to assessing the methods in terms of segmentation accuracy, we propose to also evaluate the methods in terms ...
Ronny Velastegui, Maxim Tatarchenko, Sezer Karaoglu, Theo Gevers   +3 more
openaire   +3 more sources

Strategy of Triple‐Gradient in Binary Pixels for Flexible Pressure Sensing with High Sensitivity and Wide‐Range Linearity

Advanced Science, EarlyView.
A flexible pressure sensor with triple‐gradient design of conductivity, modulus, and dimension in binary micro‐dome pixels is proposed. Based on precisely‐designed CNT/PDMS matrix, the device exhibits a linear sensitivity of 974.1 kPa−1 across range up to 1.8 MPa (R2 > 0.99), offering an effective strategy for potential applications in healthcare ...
Yifan Liu, Xiao Xu, Fengming Hu, Yuanzhe Liang, Zidong Yin, Biao Qi, Ruolin Liu, Ziyi Dai, Jianyi Luo, Bingpu Zhou   +9 more
wiley   +1 more source

Trustworthy Breast Ultrasound Image Semantic Segmentation Based on Fuzzy Uncertainty Reduction. [PDF]

Healthcare (Basel), 2022
Huang K, Zhang Y, Cheng HD, Xing P.
europepmc   +1 more source

From interactive to semantic image segmentation

, 2011
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

Enhancing Super‐Resolution Spatial Transcriptomics Data by Transfer Learning

Advanced Science, EarlyView.
SpotZoomer employs a transfer‐learning‐based strategy to enhance the resolution of Visium data by leveraging available high‐resolution priors. The resulting super‐resolved maps enable sharper delineation of cell boundaries and more precise inference of cell–cell communication patterns that would otherwise remain obscured at native resolution.
Xiaoyu Li, Lihua Zhang, Wenwen Min
wiley   +1 more source

Hypothesis-based image segmentation for object learning and recognition [PDF]

, 2010
Denecke A. Hypothesis-based image segmentation for object learning and recognition. Bielefeld: Universität Bielefeld; 2010.This thesis addresses the figure-ground segmentation problem in the context of complex systems for automatic object recognition as ...
Denecke, Alexander
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