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DBTU-Net: A Dual Branch Network Fusing Transformer and U-Net for Skin Lesion Segmentation
Published 2025-01-01“…However, CNN-based models struggle with long-range feature modeling, while Transformer-based models tend to pay less attention to local information, resulting in lower boundary accuracy. To address the aforementioned issues, we propose a dual branch network fusing Transformer and U-Net (DBTU-Net). …”
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Research on 5G-TSN joint scheduling mechanism based on radio channel information
Published 2021-12-01Get full text
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Monetizing Digital Innovation in the AEC Industry: Real Estate Value Creation Through BIM and BMS Integration
Published 2025-06-01Subjects: Get full text
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Using the Petri Network to Organize Resource Sharing between Two Processors
Published 2009-03-01Subjects: Get full text
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StarCD-Net: A Remote Sensing Change Detection Method Combining StarNet and Differential Operators
Published 2025-01-01“…To overcome these problems, we propose a new model, StarCD-Net, that combines StarNet and differential operators, which uses StarNet for feature extraction and aggregates the extracted features by Multi-Layer Feature Aggregation Module (MLFA) to obtain rich information. …”
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MSAmix-Net: Diabetic Retinopathy Classification
Published 2024-01-01“…Most models are based on convolutional neural networks, but due to the small size of convolution kernels in shallow networks, the receptive field is limited, preventing the capture of global information. This limitation forces models to require more convolutional layers to expand the receptive field and capture global information related to DR. …”
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Notschool.net Uncovered: Not All It Seems
Published 2023-11-01“…This paper comments on the recent Notschool.net initiative and offers a critical perspective on the rapid growth of information and communication technology (ICT) in New Zealand schools. …”
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GIVTED-Net: GhostNet-Mobile Involution ViT Encoder-Decoder Network for Lightweight Medical Image Segmentation
Published 2024-01-01“…Nevertheless, conventional CNN layers, such as convolution and pooling, demonstrate a spatial inductive bias that constrains their ability to instantly capture global context information. To address these limitations, the GIVTED-Net model is introduced. …”
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Representing the Ring-Net in Word and Image
Published 2024-05-01“…The correspondence also signalled the need for the use of both word and image to communicate and transfer information with real accuracy. This article focuses not only on the original Ring-Net research but also on a more recent collaboration where Martin’s poems are set alongside Maclean’s ink drawings in the publication One Time in a Tale of Herring (2010). …”
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Studies on Deltamethrin Treated Mosquito Net
Published 2010-01-01“…Further, the assessment of the mode of incorporation of the deltamethrin in the fabric of the mosquito net was done, i.e. whether the deltamethrin was present as a coating on the surface of the mosquito net or it was incorporated in the bulk of the material of construction of the mosquito net. …”
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An enhanced deep learning approach for speaker diarization using TitaNet, MarbelNet and time delay network
Published 2025-07-01Get full text
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MMEFU-Net: A Mamba-Guided Multi-Encoder Fusion U-Net for Tumor Segmentation in CT Images
Published 2025-01-01“…Comprehensive experiments on five public and private benchmark datasets, encompassing both liver tumors and lung cancers, demonstrate that MMEFU-Net outperforms state-of-the-art U-Net, Transformer-based, and Mamba-based architectures. …”
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DBU-Net: Dual-Branch U-Net for Retinal Fundus Image Super-Resolution Under Complex Degradation Conditions
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SODU2-NET: a novel deep learning-based approach for salient object detection utilizing U-NET
Published 2025-05-01“…This model addresses a gap in previous work that focused primarily on complex backgrounds by employing a densely supervised encoder-decoder network. The proposed SODU2-NET employs sophisticated background subtraction techniques and utilizes advanced deep learning architectures that can discern relevant foreground information when dealing with complex backgrounds. …”
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