SympCoughNet: symptom assisted audio-based COVID-19 detection by Yuhao Lin, Xiu Weng, Bolun Zheng, Weiwei Zhang, Zhanjun Bu, Yu Zhou

“…However, most existing approaches focus solely on audio classification, often leading to suboptimal accuracy while neglecting valuable prior information, such as clinical symptoms. To address this limitation, we propose SympCoughNet, a deep learning-based COVID-19 audio classification network that integrates cough sounds with clinical symptom data. …”
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RTL-Net: real-time lightweight Urban traffic object detection algorithm by Zhiqing Cui, Jiahao Yuan, Haibin Xu, Yamei Wei, Zhenglong Ding

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Research on Buckwheat Weed Recognition in Multispectral UAV Images Based on MSU-Net by Jinlong Wu, Xin Wu, Ronghui Miao

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Dual-Path Interactive U-Net for Unsupervised Hyperspectral Image Super-Resolution by Wenchen Deng, Jianjun Liu, Jinlong Yang, Zebin Wu, Liang Xiao

“…Specifically, we use a standard U-Net and a reversed U-Net as the backbone to extract image information and generate abundance maps of the input images. …”
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Modeling Chandy–Lamport Distributed Snapshot Algorithm Using Colored Petri Net by Saeid Pashazadeh, Basheer Zuhair Jaafar Al-Basseer, Jafar Tanha

“…It is used for different applications like collecting information from a distributed system and taking checkpoints for process rollback. …”
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Enhancing Point Cloud Classification and Segmentation With Attention-Enhanced SO-PointNet++ by Gang Cheng, Chengwei Gu

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W1-Net: a highly scalable ptychography convolutional neural network by Chengye Xing, Chengye Xing, Lei Wang, Yangyang Mu, Yu Li, Yu Li, Guangcai Chang

“…To address this problem, a series of W-Net neural network models have been proposed which can robustly reconstruct the object phase information from the raw data. …”
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Medical image segmentation by combining feature enhancement Swin Transformer and UperNet by Lin Zhang, Xiaochun Yin, Xuqi Liu, Zengguang Liu

“…This paper proposes a novel medical image segmentation model, FE-SwinUper, designed to address these challenges by integrating the strengths of the Swin Transformer and UPerNet architectures. The objective is to enhance multi-scale feature extraction and improve the fusion of hierarchical organ and tissue representations through a feature enhancement Swin Transformer (FE-ST) backbone and an adaptive feature fusion (AFF) module. …”
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Forms of labour in information systems by Julian Warner

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Automatic cervical tumors segmentation in PET/MRI by parallel encoder U-net by Shuai Liu, Zheng Tan, Tan Gong, Xiaoying Tang, Hongzan Sun, Fei Shang

“…Methods A parallel encoder U-Net (PEU-Net) integrating the multi-modality information of PET/MRI was proposed to segment cervical tumor, which consisted of two parallel encoders with the same structure for PET and MR images. …”
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DA-Net: Dual Attention Network for Haze Removal in Remote Sensing Image by Namwon Kim, Il-Seok Choi, Seong-Soo Han, Chang-Sung Jeong

“…Our experimental results show that DA-Net achieves much better performance for both synthetic and real image data sets compared to the other dehazing models in terms of quantitative and qualitative evaluations.…”
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ALPD-Net: a wild licorice detection network based on UAV imagery by Jing Yang, Huaibin Qin, Jianguo Dai, Guoshun Zhang, Miaomiao Xu, Yuan Qin, Jinglong Liu

“…At the same time, a Progressive Feature Fusion Module (PFFM) is developed, where a weighted self-attention fusion strategy is employed to effectively merge detailed and semantic information from adjacent layers, thereby preventing information loss or mismatches.Results and discussionThe experimental results show that ALPD-Net achieves good detection accuracy in wild licorice identification, with precision 73.3%, recall 76.1%, and mean Average Precision at IoU=0.50 (mAP50) of 79.5%. …”
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DFF-ResNet: An Insect Pest Recognition Model Based on Residual Networks by Wenjie Liu, Guoqing Wu, Fuji Ren, Xin Kang

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CenterNet-Elite: A Small Object Detection Model for Driving Scenario by Lingling Wang, Xiang Li, Xiaoyan Chen, Bin Zhou

“…In this context, this study proposes a new model, CenterNet-Elite, to overcome these challenges. To address the issue of feature information loss resulting from multiple downsamplings during feature extraction for small objects, we introduce the spatial and channel reconstruction convolution (SCConv) into the bottleneck to reduce spatial and channel redundancy and enhance feature representation. …”
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An End-to-End CRSwNP Prediction with Multichannel ResNet on Computed Tomography by Shixin Lai, Weipiao Kang, Yaowen Chen, Jisheng Zou, Siqi Wang, Xuan Zhang, Xiaolei Zhang, Yu Lin

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Efficient Generative-Adversarial U-Net for Multi-Organ Medical Image Segmentation by Haoran Wang, Gengshen Wu, Yi Liu

“…This paper introduces a novel medical image-segmentation framework named Efficient Generative-Adversarial U-Net (EGAUNet), designed to facilitate rapid and accurate multi-organ labeling. …”
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Retinex-Net mine image enhancement algorithm based on adaptive illumination estimation by Feng TIAN, Tingting CHEN, Xiaopei LIU

“…However, the images collected by these systems are often affected by low brightness, uneven illumination, information loss, blurred details and other issues caused by dust, water mist and light sources. …”
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Master of Information Science (MIS) by Kabale University

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EHAFF-NET: Enhanced Hybrid Attention and Feature Fusion for Pedestrian ReID by Jun Yang, Yan Wang, Haizhen Xie, Jiayue Chen, Shulong Sun, Xiaolan Zhang

“…We propose a pedestrian re-identification method called EHAFF-NET, which integrates an enhanced hybrid attention mechanism and multi-branch feature fusion. …”
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Digital tools for informed living by Chiara Tonelli, Barbara Cardone, Giuliana Nardi

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