Results 111 to 120 of about 7,061 (200)

Terrestrial Ecosystem Detection Based on Deep Learning Framework and Satellite Image Geographical Information

Geoscience Data Journal, Volume 13, Issue 3, July 2026.
The proposed deep learning framework integrates ResNet‐50 and LSTM models to detect and classify terrestrial ecosystems from satellite imagery. The workflow begins with image preprocessing using bilateral, guided, and median filters to enhance image quality and preserve edges.
Liang Dong, Fan Lei, Dongliang Huang, Yuye Gong, Jide Wei, Wenjing She   +5 more
wiley   +1 more source

SE‐Swin: An improved Swin‐Transfomer network of self‐ensemble feature extraction framework for image retrieval

IET Image Processing
The Swin‐Transformer is a variant of the Vision Transformer, which constructs a hierarchical Transformer that computes representations with shifted windows and window multi‐head self‐attention.
Yixuan Xu, Xianbing Wang, Hua Zhang, Hai Lin   +3 more
doaj   +1 more source

Swin Routiformer: Moss Classification Algorithm Based on Swin Transformer With Bi-Level Routing Attention

IEEE Access
Accurate classification of moss species is essential for progress in ecology and biology. However, traditional methods for classifying moss require significant expertise, and current deep learning techniques struggle due to limited dataset diversity and ...
Peichen Li, Huiqin Wang, Zhan Wang, Ke Wang, Chong Wang   +4 more
doaj   +1 more source

GBT‐SAM: A Parameter‐Efficient Depth‐Aware Model for Generalizable Brain Tumor Segmentation on mp‐MRI

International Journal of Imaging Systems and Technology, Volume 36, Issue 4, July 2026.
ABSTRACT Gliomas are aggressive brain tumors that require accurate imaging‐based diagnosis, where automated segmentation plays a central role in assessing tumor morphology and guiding treatment decisions. Manual delineation of gliomas is time‐consuming and prone to variability, motivating the use of deep learning to improve consistency and alleviate ...
Cecilia Diana‐Albelda, Roberto Alcover‐Couso, Álvaro García‐Martín, Jesus Bescos, Marcos Escudero‐Viñolo   +4 more
wiley   +1 more source

Transformers meet CNNs for insights into breast mass classification from histopathological images

Frontiers in Artificial Intelligence
IntroductionBreast cancer remains one of the leading causes of cancer-related deaths among women worldwide, highlighting the critical need for accurate histopathological diagnosis and reliable decision-support systems to improve diagnostic sensitivity ...
Vatsala Anand, Ajay Khajuria
doaj   +1 more source

Benchmarking Hybrid CNN‐Transformer Versus Pure Transformer Architectures for Accelerated Hyperpolarized 129Xe MRI Reconstruction

Journal of Magnetic Resonance Imaging, Volume 64, Issue 1, Page 266-280, July 2026.
ABSTRACT Background Hyperpolarized 129Xe MRI faces technical challenges including low signal‐to‐noise ratio and breath‐hold constraints. Current literature focuses on proprietary deep learning methods or image‐domain enhancements. Purpose To present a comprehensive evaluation of transformer and hybrid CNN‐transformer architectures integrating dual ...
Ramtin Babaeipour, Matthew S. Fox, Grace Parraga, Alexei Ouriadov   +3 more
wiley   +1 more source

Swin Transformer With Spatial and Local Context Augmentation for Enhanced Semantic Segmentation of Remote Sensing Images

IEEE Open Journal of Signal Processing
Semantic segmentation of remote sensing images is extensively used in crop cover and type analysis, and environmental monitoring. In the semantic segmentation of remote sensing images, owning to the specificity of remote sensing images, not only the ...
Rong-Xing Ding, Yi-Han Xu, Gang Yu, Wen Zhou, Ding Zhou   +4 more
doaj   +1 more source

Generative Artificial Intelligence and Large Language Models in Clinical Oncology

MedComm, Volume 7, Issue 7, July 2026.
By integrating multimodal data, including medical imaging, pathology, omics, and electronic health records, generative AI and LLMs support cancer diagnosis, treatment planning, and follow‐up management. These technologies also enhance physician–patient communication, improve personalized treatment strategies, and leverage intelligent agent automation ...
Yunfang Yu, Zhenhui Zhao, Zehua Wang, Ruichong Lin, Yujie Tan, Yongjian Chen, Ting Li, Daniel Baptista‐Hon, Xiaoxi Zhang, Chuan Wu, Man Tong, Lijun Zheng, Junyan Wu, Olivia Monteiro, Kang Zhang   +14 more
wiley   +1 more source

Transformer face recognition method based on multi-level feature fusion

四川大学学报. 自然科学版
The convolutional operation in a convolutional neural network only captures local information, whereas the Transformer retains more spatial information and can create long-range connections of images. In the application of vision field, Transformer lacks
XIA Gui-Shu, ZHU Zi-Han, WEI Yong-Chao, ZHU Hong-Chao, XU Wei-Qi   +4 more
doaj  

A pipeline to compile expert‐verified datasets of digitised herbarium specimens for automated plant identification to accelerate taxonomy

PLANTS, PEOPLE, PLANET, Volume 8, Issue 4, Page 1145-1159, July 2026.
Understanding and protecting plant life is essential for tackling the twin challenges of biodiversity loss and climate change. To support this, we have developed a new digital approach that helps identify plant species more quickly and accurately.
Jed Arno, Jérémie Morel, Fitiavana Rasaminirina, Juliene de Fátima Maciel‐Silva, Daniel Cahen, Damon P. Little, Daniele Silvestro, Alexandre Antonelli, Olwen Grace, Li Zhang, Isabel Larridon   +10 more
wiley   +1 more source