Results 91 to 100 of about 206,029 (232)

FML-Swin: An Improved Swin Transformer Segmentor for Remote Sensing Images

IEEE Access
Semantic segmentation of urban remote sensing images is a very challenging task. Due to the complex background, occlusion overlap and small scale target of urban remote sensing image, the semantic segmentation results have some defects such as target confusion and similarity, target boundary ambiguity, and small scale target omission.
Tianren Wu, Wenqin Deng, Rui Lin, Junzhe Jiang 0004, Xueyun Chen   +4 more
openaire   +2 more sources

A Lightweight Deep Neural Network for Individual Leopard Identification: Supporting Movement Ecology in the Taihang Mountains of Henan

Integrative Zoology, EarlyView.
We developed LeoNet, a lightweight deep learning model for leopard individual identification. It achieved 97.42% accuracy and was robust to age‐related pattern changes and unfamiliar individuals. Applied to camera‐trap data from the Taihang Mountains, LeoNet identified 41 wild North China leopards and generated individual‐level records to support ...
Jing He, Guoqing Shangguan, Yu Li, Fuming Ma, Zhishu Xiao, Mingliang Fan, Zhuo Chen, Junzhan Ren, Yingfeng Ren, Yunlong Wang, Tianping Wang, Hua Yang, Hualei Shen, Xiaohong Chen   +13 more
wiley   +1 more source

Visualizing Image Segmentation Network Behavior Through the Lens of Scale Space Analysis

Computer Graphics Forum, EarlyView.
Abstract Deep neural networks are widely used for image segmentation, also in sensitive applications such as medical imaging or autonomous driving. However, few explainable AI methods are available that help developers understand such networks beyond classification.
A. C. Mikliss, T. Schultz
wiley   +1 more source

Swin–UNet++: A Nested Swin Transformer Architecture for Location Identification and Morphology Segmentation of Dimples on 2.25Cr1Mo0.25V Fractured Surface

, 2021
The precise identification of micro-features on 2.25Cr1Mo0.25V steel is of great significance for understanding the mechanism of hydrogen embrittlement (HE) and evaluating the alloy’s properties of HE resistance.
Mengyu Chai, Pan Liu, Yu Zhang, Zelin Han, Yan Song   +4 more
core   +1 more source

Comparing deep learning models for butterfly and moth (Lepidoptera) species identification

Insect Conservation and Diversity, EarlyView.
Deep learning models open new possibilities for the processing of image‐based species records. We used high‐performance computing to compare 40 models for butterfly and moth species identification based on a citizen science dataset with over 500,000 images of 162 species.
Friederike Barkmann, Andreas Lindner, Johannes Rüdisser   +2 more
wiley   +1 more source

Compilation (Open@Swin)

, 2015
Compilation of interviews from the Open@Swin series: Conversations about open educational resources and open access at ...
Emma L. Donaldson, Copyright Office, Lyndon Walker, Dan Hunter, Kim Tairi, Birgit Loch, Mike Keppell, Robin Wright   +7 more
core   +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

Multi-dimension unified Swin Transformer for 3D Lesion Segmentation in Multiple Anatomical Locations [PDF]

, 2023
In oncology research, accurate 3D segmentation of lesions from CT scans is essential for the modeling of lesion growth kinetics. However, following the RECIST criteria, radiologists routinely only delineate each lesion on the axial slice showing the ...
Liu, Yiqiao, Baumgartner, Richard, Chen, Antong, Goldmacher, Gregory, Wang, Shubing, Pan, Shaoyan, Tomaszewski, Michal, Halek, Sarah, Yuan, Jianda   +8 more
core  

Deep Learning Models for Detection of Periapical Radiolucent Lesions on Panoramic Radiographs: A Systematic Review and Meta‐Analysis

International Endodontic Journal, EarlyView.
ABSTRACT Background Panoramic radiographs are used routinely to screen dental conditions and treatment patterns. Recently, numerous studies have suggested that deep learning (DL) models can be utilized for analysing panoramic radiographs. Objective This review aimed to evaluate the accuracy of DL models in detecting periapical radiolucent lesions (PRLs)
Ibrahim Ali Ahmad, Raidan Ba‐Hattab, Sadeq Ali Al‐Maweri, Faleh Tamimi   +3 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