Using U-Net models in deep learning for brain tumor detection from MRI scans by Minh Khiem Nguyen, Phuoc Huy Tran, Tan Tai Phan

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LSL-SS-Net: level set loss-guided semantic segmentation networks for landslide extraction by Yueheng Yang, Zelang Miao, Xiaojing Li, Hua Zhang, Shuai Chen

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TuSegNet: A Transformer-Based and Attention-Enhanced Architecture for Brain Tumor Segmentation by Mir Nafiul Nagib, Rahat Pervez, Afsana Alam Nova, Hadiur Rahman Nabil, Zeyar Aung, M. F. Mridha

“…Brain tumor segmentation is crucial in medical imaging, allowing informed diagnosis and treatment planning. In this study, we propose TuSegNet, a new transformer-based and attention-enhanced architecture for robust brain tumor segmentation. …”
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FaultVitNet: A Vision Transformer Assisted Network for 3D Fault Segmentation by Chao Li, Sergey Fomel, Yangkang Chen, Robin Dommisse, Alexandros Savvaidis

“…The proposed vision‐transformer‐assisted network (FaultVitNet) exploits a hybrid attention mechanism for feature extraction, enabling the network to capture the global distribution information of faults. …”
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Improved Low-Light Image Feature Matching Algorithm Based on the SuperGlue Net Model by Fengchao Li, Yu Chen, Qunshan Shi, Ge Shi, Hongding Yang, Jiaming Na

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Millimeter Wave SAR Imaging Denoising and Classification by Combining Image-to-Image Translation With ResNet by Pham The Hien, Ic-Pyo Hong

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A hybrid framework for colorectal cancer detection and U-Net segmentation using polynetDWTCADx by Akella S Narasimha Raju, K Venkatesh, Makineedi Rajababu, Ranjith Kumar Gatla, Marwa M. Eid, Enas Ali, Nataliia Titova, Ahmed B. Abou Sharaf

“…We can also employ the semantic segmentation algorithms of the U-Net architecture to accurately identify and segment cancerous colorectal regions. …”
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MAVM-UNet: multiscale aggregated vision MambaU-Net for field rice pest detection by Congqi Zhang, Ting Zhang, Guanyu Shang

“…A multiscale aggregated vision MambaU-Net (MAVM-UNet) model for rice pest detection is constructed. …”
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Estimating Subsurface Thermohaline Structure in the Tropical Western Pacific Using DO-ResNet Model by Xianmei Zhou, Shanliang Zhu, Wentao Jia, Hengkai Yao

“…This paper proposes an improved double-output residual neural network (DO-ResNet) model to concurrently estimate the subsurface temperature (ST) and subsurface salinity (SS) in the tropical Western Pacific using multi-source remote sensing data, including sea surface temperature (SST), sea surface salinity (SSS), sea surface height anomaly (SSHA), sea surface wind (SSW), and geographical information (including longitude and latitude). …”
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SFMattingNet: A Trimap-Free Deep Image Matting Approach for Smoke and Fire Scenes by Shihui Ma, Zhaoyang Xu, Hongping Yan

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IRSD-Net: An Adaptive Infrared Ship Detection Network for Small Targets in Complex Maritime Environments by Yitong Sun, Jie Lian

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A novel approach of drowsiness levels detection using Vis-Net combined with facial emotion by Thuong-Cang Phan, Anh-Cang Phan, Ngoc-Hoang-Quyen Nguyen

“…Unlike traditional binary classification methods that simply distinguish between “drowsy” and “not drowsy,” the proposed Vis-Net model is a hybrid deep neural network that is a combination of the Vision Transformer and neural networks, including MobileNet-V2, Inception-V3, ResNet152-V2, NASNetLarge, and DenseNet. …”
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Open museum: between visibility and visuality. Composing nets and views of afection. from fragments to constelations by Lilian Amaral

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MDE-Net: Multi-Layer Depth Extraction Network With Attention Mechanism for Medical Image Segmentation by Xiaokang Ding, Ling Dong, Yingyu Ji, Ke'Er Qian

“…Finally, in the decoder part, we design the SE-MultiResConv that combines multi-scale residual convolution with SE attention mechanism to improve segmentation accuracy and prevent the loss of detail information during up-sampling. In extensive experiments, we conducted detailed tests on two publicly available medical image datasets to rigorously evaluate the performance of our proposed MDE-Net. …”
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DSGAU: Dual-Scale Graph Attention U-Nets for Hyperspectral Image Classification With Limited Samples by Hongzhuang Ji, Leying Song, Zhaohui Xue, Hongjun Su

“…Nevertheless, prevalent graph pooling techniques often employ single-scale strategies that inadequately capture multiscale features, potentially leading to information loss or redundancy. To address this issue, we propose a dual-scale graph attention U-Nets for HSI classification with limited samples. …”
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Development, usability and acceptability of an integrated eHealth system for spondyloarthritis in the Netherlands (SpA-Net) by Astrid van Tubergen, Casper Webers, Annelies Boonen, Esther Beckers, Yvonne van Eijk-Hustings, Harald Vonkeman, Mart van de Laar

“…Care providers appreciated the additional information for (preparing) consultations. Barriers were the initial time required to adopt the EMR and the quantity of data entry.Conclusion SpA-Net enables monitoring of patients with SpA and real-life data collection, and could help improve knowledge and optimise communication between patients and care providers. …”
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Contextualizing Wilson’s Information Behavior model in Seeking Indigenous Information for HIV prevention among Adolescents in Secondary schools, Uganda by Olivia Nina, Rugambwa, Lyaka, Martha, Mutibwa, Lois Nankya

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High-precision pest and disease detection in greenhouses using the novel IM-AlexNet framework by Ruipeng Tang, Narendra Kumar Aridas, Mohamad Sofian Abu Talip, Jianbu Yang, Jianrui Tang

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GRU2-Net: Global response double U-shaped network for lesion segmentation in ultrasound images by Xiaokai Jiang, Xuewen Ding, Jinying Ma, Chunyu Liu, Xinyi Li

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Exploring multiple optimization algorithms in transfer learning with EfficientNet models for agricultural insect classification by Hoang-Tu Vo, Nhon Nguyen Thien, Kheo Chau Mui, Huan Lam Le, Phuc Pham Tien

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