Results 141 to 150 of about 66,833 (314)

Hierarchical Context Learning of object components for unsupervised semantic segmentation

Unsupervised Semantic Segmentation (USS) aims to learn semantically rich and dense representations without relying on labels. Recent advances in self-supervised learning have demonstrated the potential of pretrained vision transformers to capture patch ...
Tuxworth, Gervase, Zhou, Jun, Zhang, Jue, Bao, Dong, Gao, Yongsheng   +4 more
core   +1 more source

A Foundation Model Based CT Biomarker for Non‐Invasive Prediction of Response to Neoadjuvant Immunochemotherapy in Non‐Small Cell Lung Cancer

Advanced Science, EarlyView.
This study introduces a foundation model‐based biomarker for risk stratification of pathological response in non‐small cell lung cancer. A Vision Mamba super‐resolution model standardizes heterogeneous CT images. A multi‐task Swin Transformer then fine‐tunes a pre‐trained lung foundation model to jointly optimize tumor segmentation and response ...
Yanglan Xu, Shuchang Zhou, Qin Peng, Xiao Bao, Xiaodan Ye, Ahmet Görkem Er, Tong Tong, Mirabela Rusu, Yajia Gu, Mailin Chen, Jing Gong   +10 more
wiley   +1 more source

Large Language Model‐Informed Dual‐Track AI Framework for the Synergistic Design of Crack‐Free and High‐Strength Superalloys

Advanced Science, EarlyView.
This paper illustrates a knowledge‐augmented dual‐track AI framework for advanced superalloy design. First, Large Language Models translate metallurgical heuristics into explicit rules to rapidly prune a vast compositional search space. Subsequently, LLM‐distilled priors safely guide a reinforcement learning agent during autonomous process optimization,
Jian Yao, Junkang Wu, Jie Su, Fuzhu Wang, Zi Wang, Li Wang, Liming Tan, Lan Huang, Feng Liu, Yong Liu   +9 more
wiley   +1 more source

Semantic Segmentation with Spreading Scribbles

Hand-annotating medical images with segmentation masks requires an immense amount of time and effort from clinical experts. Replacing full masks with a simpler annotating gesture can mitigate annotation costs. This can come in the form of a scribble, and leads to weakly supervised training scenarios.
Yeva Gabrielyan, Varduhi Yeghiazaryan, Irina Voiculescu   +2 more
openaire   +1 more source

Decoupling Continual Semantic Segmentation

Proceedings of the AAAI Conference on Artificial Intelligence
Continual Semantic Segmentation (CSS) requires learning new classes without forgetting previously acquired knowledge, addressing the fundamental challenge of catastrophic forgetting in dense prediction tasks. However, existing CSS methods typically employ single-stage encoder-decoder architectures where segmentation masks and class labels are tightly ...
Yifu Guo, Yuquan Lu, Wentao Zhang 0005, Zishan Xu, Dexia Chen, Siyu Zhang, Yizhe Zhang 0001, Ruixuan Wang   +7 more
openaire   +2 more sources

SEMANTIC SEGMENTATION OF MICROSCOPIC BLOOD IMAGE DATA USING SELF-TRAINING TO AUGMENT SMALL TRAINING SETS AND ITS APPLICATION FOR COUNTING CELLS

, 2019
Semantic segmentation is a computer vision task of assigning a label describing the content to each pixel in an image. There has been a lot of progress in this area using deep neural networks with an encoder-decoder structure.
Luo, Junliang
core  

CD177 Deficiency Defines a Stable Subtype of Human Neutrophil Granulocytes with Tumor Promoting Activity

Advanced Science, EarlyView.
Human neutrophils exist as two epigenetically imprinted subtypes defined by stable CD177 expression or absence — a ratio that persists across time, circadian rhythms, and inflammation. CD177− neutrophils display a distinct molecular landscape enriched in arginase 1 and lipid metabolism markers, accumulate in head‐and‐neck tumors, and associate with ...
Marcel Jung, Alexander Beer, Susmita Ghosh, Ekaterina Pylaeva, Belal Alshaar, Tobias Tertel, Nils Bastian Leimkühler, Thomas Schroeder, Janine Gronewold, Nina Hagemann, Ayan Mohamud Yusuf, Benedikt Frank, Yiqiao Zhang, Dennis Nagel, Kim Schloeßer, Laura Karsch, Emily Hedtfeld, Sabrina Lohmann, Kathrin Blank, Andreas Kraus, Max Krumbein, Nastassia Kabankova, Hongxiao Wang, Almke Bader, Mathis Richter, Fengjun Zhang, Raphael Chevre, Bernd Giebel, Stephan Lang, Anika Grüneboom, Daniela Maier‐Begandt, Anja Hasenberg, Oliver Soehnlein, Hans Christian Reinhardt, Sven Heiles, Jianxu Chen, Jadwiga Jablonska, Albert Sickmann, Dirk M. Hermann, Matthias Gunzer   +39 more
wiley   +1 more source

Semantic Segmentation For Aerial Images

International Journal of Research Publication and Reviews
Semantic segmentation of aerial imagery plays a critical role in modern urban planning, environmental monitoring, and the development of smart cities. This project presents an interactive webbased application that performs semantic segmentation on high-resolution aerial images using a deep learning-based U-Net model.
Dr. B. Harika, M. Bharath, K. Himneesh
openaire   +2 more sources

A Machine Vision‐Guided Microphysiological Platform With Automated Microfluidics Enables Longitudinal Biomarker Monitoring and Emulation of Translationally Relevant Exposure Scenarios

Advanced Science, EarlyView.
A pneumatically actuated multi‐tissue microphysiological system is integrated with AI‐based machine vision and automatic sampling and replenishment systems. The platform allows for the emulation of translationally relevant long‐term pharmacokinetic exposure scenarios for multiple weeks while enabling longitudinal monitoring of response biomarkers ...
Jibbe Keulen, Yi Zhong, Laura Dangel, Sonia Youhanna, Reza Zandi Shafagh, Jinhye Ryu, Domnica‐Gabriela Gurau, Mathias Haag, Thomas E. Mürdter, Yingxin Liang, Iro Beligiani, Nicole Ziegler, Sabine Willems, Nayere Taebnia, Wouter van der Wijngaart, Volker M. Lauschke   +15 more
wiley   +1 more source

Brain-Inspired Synergistic Adversarial Framework for Style Transfer-Guided Semantic Segmentation in Cross-Domain Remote Sensing Imagery

Remote Sensing
Domain shifts pose significant challenges for cross-domain semantic segmentation in high-resolution remote sensing imagery. Inspired by the cognitive mechanisms of the human brain, we propose a Brain-Inspired Style Transfer and Semantic Segmentation ...
Xinyao Wang, Haitao Wang, Yuqian Jing, Xiaodong Li, Xianming Yang   +4 more
doaj   +1 more source