Results 91 to 100 of about 8,876 (216)

Super‐Resolution of Planetary Images Based on Generative Adversarial Network

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Currently, satellite imagery serves as the primary means of observing terrestrial planets such as the Mars, the Moon, and Mercury. Enhancing the resolution and quality of these images can provide more detailed insights into planetary surfaces. However, improvements in image quality are often limited by the constraints of sensor technology and ...
Xiaoran Zhang, Yiran Wang, Miao Zhuo
wiley   +1 more source

KLASIFIKASI PENYAKIT BATU GINJAL MENGGUNAKAN SHIFTED WINDOWS TRANSFORMER (SWIN TRANSFORMER) [PDF]

Batu ginjal adalah masalah urologi umum yang dapat menyebabkan komplikasi serius jika tidak terdeteksi sejak dini. Proses diagnosis tradisional sangat bergantung pada interpretasi manual ultrasonografi, yang rentan terhadap kesalahan dan bisa memakan ...
Prastyo, Alfian Bima
core  

Off-line identifying Script Writers by Swin Transformers and ResNeSt-50

ELCVIA Electronic Letters on Computer Vision and Image Analysis
In this work, we present two advanced models for identifying script writers, leveraging the power of deep learning. The proposed systems utilize the new vision Swin Transformer and ResNeSt-50.
Afef Kacem Echi, Takwa Ben Aïcha Gader
doaj   +1 more source

FS‐Mamba: Feature‐wise scanning Mamba UNet for automatic image segmentation in liver tumor radiotherapy

Journal of Applied Clinical Medical Physics, Volume 27, Issue 7, July 2026.
Abstract Background Medical image segmentation is fundamental to radiotherapy planning, yet accurate delineation of organs at risk and tumor targets remain challenging due to anatomical variability and low soft‐tissue contrast in CT images. Purpose To develop a lightweight, high‐precision automatic segmentation network that meets the dual clinical ...
Peijun Yin, Xueren Zhang, Xin Liu, Zekun Jiang, Qingtao Qiu, Yong Yin, Zhenjiang Li   +6 more
wiley   +1 more source

A Recognition and Classification Method for Underground Acoustic Emission Signals Based on Improved CELMD and Swin Transformer Neural Networks

Applied Sciences
To address the challenges in processing and identifying mine acoustic emission signals, as well as the inefficiency and inaccuracy issues prevalent in existing methods, an enhanced CELMD approach is adopted for preprocessing the acoustic emission signals.
Xuebin Xie, Yunpeng Yang
doaj   +1 more source

Toward Precision Biodiversity Detection: An Edge‐Deployable Framework for Mitigating Data Redundancy

Ecology and Evolution, Volume 16, Issue 7, July 2026.
This research introduces the WS—YOLO, a lightweight and high—efficiency wildlife detection model that is specifically optimized for edge deployment within camera trap systems. The goal is to enable both false trigger filtering and accurate animal detection within a single model, tailored for low‐power edge deployment. The proposed method contributes to
Huihui Sun, Yang Liu, Yang Wang
wiley   +1 more source

Pavement Crack Detection Based on the Improved Swin-Unet Model

Buildings
Accurate pavement surface crack detection is crucial for analyzing pavement survey data and the development of maintenance strategies. On the basis of Swin-Unet, this study develops the improved Swin-Unet (iSwin-Unet) model with the developed skip ...
Song Chen, Zhixuan Feng, Guangqing Xiao, Xilong Chen, Chuxiang Gao, Mingming Zhao, Huayang Yu   +6 more
doaj   +1 more source

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

Vision‐Language Models for Automated Chest X‐ray Interpretation: Leveraging ViT and GPT‐2

Engineering Reports
Radiology plays a pivotal role in modern medicine due to its non‐invasive diagnostic capabilities. However, the manual generation of unstructured medical reports is time‐consuming and prone to errors.
Md. Rakibul Islam, Md. Zahid Hossain, Mustofa Ahmed, Most. Sharmin Sultana Samu   +3 more
doaj   +1 more source

A novel framework for rosacea detection using Swin Transformers and explainable artificial intelligence

Alexandria Engineering Journal
Accurate and efficient diagnosis of skin rosacea is crucial in dermatological healthcare, yet remains challenging due to the need for precise classification and interpretability.
Anjali T, S. Abhishek, Remya S
doaj   +1 more source