Improved U-Net for Precise Gauge Dial Segmentation in Substation Inspection Systems: A Study on Enhancing Accuracy and Robustness by Wan Zou, Yiping Jiang, Wenlong Liao, Songhai Fan, Yueping Yang, Jin Hou, Hao Tang

“…These improvements enable the network to more accurately detect target regions within dial images, significantly enhancing segmentation accuracy and robustness. Experimental results demonstrate that the proposed method outperforms traditional U-Net models in segmentation tasks, achieving superior precision in segmenting scales and pointers, effectively addressing issues of low precision and poor segmentation, and making it suitable for real-time substation inspection systems.…”
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TransRNetFuse: a highly accurate and precise boundary FCN-transformer feature integration for medical image segmentation by Baotian Li, Jing Zhou, Fangfang Gou, Jia Wu

“…The objective of this method is to address the issues associated with the extraction of local key features and the accurate delineation of boundaries in medical image segmentation. …”
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A superpixel based self-attention network for uterine fibroid segmentation in high intensity focused ultrasound guidance images by Shen Wen, Dong Zhang, Yuting Lei, Yan Yang

“…To address these issues, we proposed the superpixel based attention network, a network integrating superpixels and self-attention mechanisms that can automatically segment tumor regions in ultrasound guidance images. …”
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MFFP-Net: Building Segmentation in Remote Sensing Images via Multi-Scale Feature Fusion and Foreground Perception Enhancement by Huajie Xu, Qiukai Huang, Haikun Liao, Ganxiao Nong, Wei Wei

“…The accurate segmentation of small target buildings in high-resolution remote sensing images remains challenging due to two critical issues: (1) small target buildings often occupy few pixels in complex backgrounds, leading to frequent background confusion, and (2) significant intra-class variance complicates feature representation compared to conventional semantic segmentation tasks. …”
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Robust Multi-Input Multi-Output Analysis for Crop Row Segmentation and Furrow Line Detection in Diverse Agricultural Fields by Muhammad Ibrahim Zain Ul Abideen, Dewa Made Sri Arsa, Talha Ilyas, Hyunggi Jo, Sang Cheol Kim, Hyongsuk Kim

“…Previous methods often focused on specific furrow types, leading to issues with generalization and adaptability. This paper introduces a comprehensive deep-learning model designed to detect furrow centerlines across diverse types of furrows, thereby improving accuracy and robustness. …”
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A New Pallet-Positioning Method Based on a Lightweight Component Segmentation Network for AGV Toward Intelligent Warehousing by Bin Wu, Shijie Wang, Yi Lu, Yang Yi, Di Jiang, Mengmeng Qiao

“…This, in turn, reduces the overall operational efficiency of the warehouse. To address this issue, this paper proposes a lightweight component segmentation network using a dual-attention mechanism to achieve precise segmentation of the pallet’s stringer board and accurate localization of the pallet slots. …”
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Enhancing Clinical Assessment of Skin Ulcers with Automated and Objective Convolutional Neural Network-Based Segmentation and 3D Analysis by Rosanna Cavazzana, Angelo Faccia, Aurora Cavallaro, Marco Giuranno, Sara Becchi, Chiara Innocente, Giorgia Marullo, Elia Ricci, Jacopo Secco, Enrico Vezzetti, Luca Ulrich

“…This study introduces a method for automatically detecting and segmenting skin ulcers using a Convolutional Neural Network and two-dimensional images. …”
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Res50-SimAM-ASPP-Unet: A Semantic Segmentation Model for High-Resolution Remote Sensing Images by Jiajing Cai, Jinmei Shi, Yu-Beng Leau, Shangyu Meng, Xiuyan Zheng, Jinghe Zhou

“…To address these issues, this study introduces the Res50-SimAM-ASPP-Unet model, a semantic segmentation approach for high-resolution remote sensing image processing tasks. …”
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A segmentation-combination data augmentation strategy and dual attention mechanism for accurate Chinese herbal medicine microscopic identification by Xiaoying Zhu, Xiaoying Zhu, Guangyao Pang, Guangyao Pang, Xi He, Xi He, Yue Chen, Yue Chen, Zhenming Yu

“…A segmentation-combination data augmentation strategy is employed to expand and balance datasets, capturing comprehensive feature sets. …”
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Enhanced unsupervised domain adaptation with iterative pseudo-label refinement for inter-event oil spill segmentation in SAR images by Guangyan Cui, Jianchao Fan, Yarong Zou

“…The imaging features of oil spills in synthetic aperture radar (SAR) images have significant differences due to factors such as marine environment, SAR sensors, oil film thickness and types, which makes it difficult to obtain a generalized model, and the limited number of SAR images obtained from new oil spill events hampers the effective training of deep learning networks. To solve these issues, an enhanced unsupervised domain adaptation with iterative pseudo-label refinement (EUDA-PLR) approach is proposed for inter-event oil spill SAR image segmentation. …”
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Application of the U-Net Deep Learning Model for Segmenting Single-Photon Emission Computed Tomography Myocardial Perfusion Images by Ahmad Alenezi, Ali Mayya, Mahdi Alajmi, Wegdan Almutairi, Dana Alaradah, Hamad Alhamad

“…Detection and diagnosis of CAD are complex processes requiring precise and accurate image processing. Proper segmentation is critical for accurate diagnosis, but segmentation issues can pose significant challenges, leading to diagnostic difficulties. …”
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The influence of image selection and segmentation on the extraction of lung cancer imaging radiomics features using 3D-Slicer software by Chunmei Liu, Yuzheng He, Jianmin Luo

“…For example, image segmentation is manually performed based on the lung window or automatically performed through the mediastinal window. …”
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Automatic Reading Method for Analog Dial Gauges with Different Measurement Ranges in Outdoor Substation Scenarios by Yueping Yang, Wenlong Liao, Songhai Fan, Jin Hou, Hao Tang

“…However, existing dial reading recognition algorithms face significant errors in complex scenarios and struggle to adapt to dials with different measurement ranges. To address these issues, this paper proposes an automatic reading method for analog dial gauges consisting of two stages: dial segmentation and reading recognition. …”
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Deep Learning-Based Instance Segmentation of Galloping High-Speed Railway Overhead Contact System Conductors in Video Images by Xiaotong Yao, Huayu Yuan, Shanpeng Zhao, Wei Tian, Dongzhao Han, Xiaoping Li, Feng Wang, Sihua Wang

“…This work expands upon the YOLO11-seg model and introduces an instance segmentation approach for galloping video and image sensor data of OCS conductors. …”
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Le cadre politico-institutionnel des migrations antillaises : des dynamiques différenciées dans un contexte géopolitique segmenté by Cédric Audebert

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Squamous cell carcinoma in situ of the cervix with superficial intraepithelial extension to the endometrium of lower uterine segment: A rare presentation by Rajeshwari K Muthusamy, Sangita S Mehta

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NasalSeg: A Dataset for Automatic Segmentation of Nasal Cavity and Paranasal Sinuses from 3D CT Images by Yichi Zhang, Jing Wang, Tan Pan, Quanling Jiang, Jingjie Ge, Xin Guo, Chen Jiang, Jie Lu, Jianning Zhang, Xueling Liu, Mei Tian, Yuan Qi, Yuan Cheng, Chuantao Zuo

“…A significant challenge in this field is the lack of publicly available clinical datasets for research. To address this issue, we introduce NagalSeg, the first large-scale, publicly available dataset for nasal cavity and paranasal sinus segmentation. …”
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Optimal Scheduling and Compensation Pricing Method for Load Aggregators Based on Limited Peak Shaving Budget and Time Segment Value by Hanyu Yang, Zhihao Sun, Xun Dou, Linxi Li, Jiancheng Yu, Xianxu Huo, Chao Pang

“…However, due to the randomness of supply and demand, fluctuations in peak shaving demand occur, making it a significant technical challenge to meet peak shaving needs under limited budget allocations. To address this issue, this paper first conducts a clustering analysis of various adjustable load characteristics to derive typical electricity consumption curves, and then proposes a differentiated calculation method for the value of multi-time-segment peak shaving. …”
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Overall Lifting Construction Control Method for Large-Segment Steel Arch Bridges Based on Unstressed State Control Theory by Zhongpei Li, Xuetao Dong, Hairong Chen, Liangjun Chi, Zhicheng Zhang

“…The construction method of first splicing the low brackets and then lifting steel arch bridges has become increasingly popular, and its construction control has become a key issue. According to the unstressed state control theory, both the horizontal displacement and rotation angle at the lifted arch segment ends should be approximately 0 during the lifting process. …”
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Enhancing precision in multiple sclerosis lesion segmentation: A U-net based machine learning approach with data augmentation by Oezdemir Cetin, Berkay Canel, Gamze Dogali, Unal Sakoglu

“…The proposed algorithm employs Convolutional Neural Networks (CNNs) in the form of U-Net architecture, a renowned model for biomedical image segmentation. To address the issue of insufficient training data, data augmentation techniques have been implemented, enhancing the diversity and volume of the training set. …”
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