Computer-aided diagnosis of hepatic cystic echinococcosis based on deep transfer learning features from ultrasound images by Miao Wu, Chuanbo Yan, Gan Sen

“…And each subtype has different treatment methods. An accurate diagnosis is the prerequisite for effective HCE treatment. …”
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Exploring Transfer Learning for Anthropogenic Geomorphic Feature Extraction from Land Surface Parameters Using UNet by Aaron E. Maxwell, Sarah Farhadpour, Muhammad Ali

“…Transfer learning between the different geomorphic datasets offered minimal benefits. …”
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S2-IFNet: A spatial-semantic information fusion network integrated with boundary feature enhancement for forest land extraction from Sentinel-2 data by Junyang Xie, Mengyao Zhang, Hao Wu, Anqi Lin, Marcos Adami, Abdul Rashid Mohamed Shariff, Yahui Guo

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Associations of greenhouse gases, air pollutants and dynamics of scrub typhus incidence in China: a nationwide time-series study by Haoyue Cao, Jianqiang Han, Weiming Hou, Juxiang Yuan

“…The Quantile-based G Computation (qgcomp) model revealed age-specific differences in susceptibility to environmental factors. …”
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CNN-based salient features in HSI image semantic target prediction by Vishal Srivastava, Bhaskar Biswas

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An Optimized 1-D CNN-LSTM Approach for Fault Diagnosis of Rolling Bearings Considering Epistemic Uncertainty by Onur Can Kalay

“…From this standpoint, the present study combined a 1-D convolutional neural network (1-D CNN) with a long short-term memory (LSTM) algorithm for classifying different ball-bearing health conditions. …”
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Target recognition in diverse synthetic aperture radar image datasets with low size weight and power processing hardware by Richard O. Lane, Wendy J. Holmes, Timothy Lamont‐Smith

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Intelligent Layout and Optimization of EV Charging Stations: Initial Configuration via Enhanced K-Means and Subsequent Refinement through Integrated GCN by H. Yang, M. Liu, J. Zou, R. Xu, J. Huang, P. Geng

“…Building on this, a layout optimization algorithm utilizing a Residual Attention Graph Convolutional Network (RAGCN) is proposed, which leverages the efficient learning capability of Graph Convolutional Networks (GCN) on graph-structured data to learn and obtain the best layout for charging stations. …”
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PlutoNet: An efficient polyp segmentation network with modified partial decoder and decoder consistency training by Tugberk Erol, Duygu Sarikaya

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Evaluation of Post Hoc Uncertainty Quantification Approaches for Flood Detection From SAR Imagery by Jakob Ludwig, Ronny Hansch

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Human activity recognition algorithms for manual material handling activities by Andreas Sochopoulos, Tommaso Poliero, Jamil Ahmad, Darwin G. Caldwell, Christian Di Natali

“…The analyzed classifiers are feedforward neural networks, 1-D convolutional neural networks, and recurrent neural networks, standard architectures in time series classification but offer different classification capabilities and computational complexity. …”
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Improvement of generalization performance of diagnostic system for drill bit abnormality in rotary percussion drilling with grad-CAM by Yuna Nakazawa, Natsuo Okada, Jo Sasaki, Lesego Senjoba, Yoko Ohtomo, Youhei Kawamura

“…This innovation allows the system to generalize across different rock and bit conditions, improving drilling efficiency and minimizing downtime in diverse environments.…”
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Fusion Mechanisms for Human Activity Recognition Using Automated Machine Learning by Ana-Cosmina Popescu, Irina Mocanu, Bogdan Cramariuc

“…Human activity recognition has been a branch of interest in the field of computer vision for decades, due to its numerous applications in different domains, such as medicine, surveillance, entertainment or human-computer interaction. …”
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Superregular Matrices over Finite Fields by Paulo Almeida, Miguel Beltrá, Diego Napp

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A Comparative Study for Localization of Forgery Regions in Images by Mustafa Ozden, Canberk Sahin

“…In total, four different methods were tested on eight datasets, and their performance was compared using metrics such as accuracy, precision, recall, dice similarity coefficient, and F1 score. …”
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CCTNet: CNN and Cross-Shaped Transformer Hybrid Network for Remote Sensing Image Semantic Segmentation by Honglin Wu, Zhaobin Zeng, Peng Huang, Xinyu Yu, Min Zhang

“…In this article, we propose a convolutional neural network (CNN) and cross-shaped transformer hybrid network (CCTNet) for semantic segmentation of high-resolution remote sensing images. …”
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EMSPAN: Efficient Multi-Scale Pyramid Attention Network for Object Counting Under Size Heterogeneity and Dense Scenarios by Phu Nguyen Phan Hai, Bao Bui Quoc, Trang Hoang

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An automated deep learning framework for brain tumor classification using MRI imagery by Muhammad Aamir, Ziaur Rahman, Uzair Aslam Bhatti, Waheed Ahmed Abro, Jameel Ahmed Bhutto, Zhonglin He

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Performance Evaluation of Various Deep Learning Models in Gait Recognition Using the CASIA-B Dataset by Nakib Aman, Md. Rabiul Islam, Md. Faysal Ahamed, Mominul Ahsan

“…Additionally, identifying individuals from different viewpoints presents a significant challenge in HGR. …”
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A multi-scale multi-channel CNN introducing a channel-spatial attention mechanism hyperspectral remote sensing image classification method by Ru Zhao, Chaozhu Zhang, Dan Xue

“…Aiming the problems that the classification performance of hyperspectral images in existing classification algorithms is highly dependent on spatial-spectral information and that detailed features are ignored in single convolutional channel feature extraction, resulting in poor generalization performance of the feature extraction model, a multi-scale multi-channel convolutional neural network (MMC-CNN) model is proposed in this paper. …”
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