Conceptual Validation of High-Precision Fish Feeding Behavior Recognition Using Semantic Segmentation and Real-Time Temporal Variance Analysis for Aquaculture by Han Kong, Junfeng Wu, Xuelan Liang, Yongzhi Xie, Boyu Qu, Hong Yu

“…In this method, we first accurately segment fish targets in the images using a semantic segmentation model. …”
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Autonomous unmanned aerial vehicles exploration for semantic indoor reconstruction using 3D Gaussian splatting by Hao Xuan Zhang, Yilin Yang, Zhengbo Zou

“…Keeping an up-to-date three-dimensional (3D) representation of buildings is a crucial yet time-consuming step for Building Information Modeling (BIM) and digital twins. To address this issue, we propose ICON (Intelligent CONstruction) drone, an unmanned aerial vehicle (UAV) designed to navigate indoor environments autonomously and generate point clouds. …”
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Advancing Alzheimer’s disease detection: a novel convolutional neural network based framework leveraging EEG data and segment length analysis by Md Nurul Ahad Tawhid, Siuly Siuly, Enamul Kabir, Yan Li

“…We also need to investigate the impact of EEG signal segment length on classification accuracy. To address these issues, a deep learning-based framework is proposed to detect AD using EEG data, focusing on determining the optimal segment length for classification. …”
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Hierarchical Optimization Segmentation and Parameter Extraction of Street Trees Based on Topology Checking and Boundary Analysis from LiDAR Point Clouds by Yuan Kou, Xianjun Gao, Yue Zhang, Tianqing Liu, Guanxing An, Fen Ye, Yongyu Tian, Yuhan Chen

“…In response to the above issues, this paper proposes a roadside tree segmentation algorithm, which first completes the scene pre-segmentation through unsupervised clustering. …”
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Enhanced YOLO11n-Seg with Attention Mechanism and Geometric Metric Optimization for Instance Segmentation of Ripe Blueberries in Complex Greenhouse Environments by Rongxiang Luo, Rongrui Zhao, Bangjin Yi

“…This study proposes an improved YOLO11n-seg instance segmentation model to address the limitations of existing models in accurately identifying mature blueberries in complex greenhouse environments. …”
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REVIEW OF RECOMMENDATIONS FOR THE MANAGEMENT OF THE ACUTE CORONARY SYNDROMES IN PATIENTS PRESENTING WITHOUT PERSISTENT ST-SEGMENT ELEVATION (ESC 2015). Part I by N. T. Vatutin, A. S. Smyrnova, D. V. Bort, L. A. Prokopenko, E. S. Uzun

“…In the August issue of European Heart Journal the guidelines, devoted to a problem of the acute coronary syndromes in patients presenting without persistent ST-segment elevation, which are developed by leading experts of the European Society of Cardiology, were published. …”
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Analyzing road traffic accidents through identification and prioritization of accident-prone areas on the dembecha to injibara highway segment in amhara region, ethiopia by Gedefaye Geremew

“…Focusing on the Dembecha-Injibara highway segment, the study employs both descriptive and inferential analyses, using the Zegeer method to calculate accident rates. …”
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Multi-Type Change Detection and Distinction of Cultivated Land Parcels in High-Resolution Remote Sensing Images Based on Segment Anything Model by Zhongxin Huang, Xiaomei Yang, Yueming Liu, Zhihua Wang, Yonggang Ma, Haitao Jing, Xiaoliang Liu

“…However, existing change detection methods based on high-resolution remote sensing imagery focus primarily on cultivation type changes, neglecting the importance of detecting parcel pattern changes. To address the issue of detecting diverse types of changes in cultivated land parcels, this study constructs an automated workflow framework for change detection, based on the unsupervised segmentation method of the SAM (Segment Anything Model). …”
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SeqConv-Net: A Deep Learning Segmentation Framework for Airborne LiDAR Point Clouds Based on Spatially Ordered Sequences by Bin Guo, Chunjing Yao, Hongchao Ma, Jie Wang, Junhao Xu

“…To address this issue, we propose a novel sequence convolution semantic segmentation architecture that integrates Convolutional Neural Networks (CNN) with a sequence-to-sequence (seq2seq) structure, termed SeqConv-Net. …”
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A Weakly Supervised and Self-Supervised Learning Approach for Semantic Segmentation of Land Cover in Satellite Images with National Forest Inventory Data by Daniel Moraes, Manuel L. Campagnolo, Mário Caetano

“…Weakly supervised and self-supervised learning approaches help address this issue by reducing dependence on fully annotated images and leveraging unlabeled data. …”
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Transfer Learning Based on Multi-Branch Architecture Feature Extractor for Airborne LiDAR Point Cloud Semantic Segmentation with Few Samples by Jialin Yuan, Hongchao Ma, Liang Zhang, Jiwei Deng, Wenjun Luo, Ke Liu, Zhan Cai

“…The existing deep learning-based Airborne Laser Scanning (ALS) point cloud semantic segmentation methods require a large amount of labeled data for training, which is not always feasible in practice. …”
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A novel MPDENet model and efficient combined loss function for real-time pixel-level segmentation detection of tunnel lining cracks by Ningyu Zhao, Yi Song, Hao Liu, Ailin Yang, Haifei Jiang, Haihong Tan

“…In this study, an efficient combined loss function was proposed to address the sample imbalance issue, and a novel lightweight model, MPDENet, was introduced for real-time pixel-level segmentation detection of tunnel lining cracks of interference backgrounds. …”
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Differential impact of two risk communications on antipsychotic prescribing to people with dementia in Scotland: segmented regression time series analysis 2001-2011. by Bruce Guthrie, Stella A Clark, Emma L Reynish, Colin McCowan, Daniel R Morales

“…Two significant UK risk communications about antipsychotic use in older people with dementia were issued in 2004 and 2009. These varied considerably in their content and dissemination, allowing examination of their differential impact.…”
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A Case of Dibothriocephalosis (<i>Dibothriocephalus latus</i>) from Iseo Lake (Northern Italy): An Update on a Persistent Sanitary Issue by Vasco Menconi, Lisa Guardone, Elena Lazzaro, Romina Bottazzo, Valeria Besutti, Patrizia Danesi, Amedeo Manfrin, Andrea Basso, Giuseppe Arcangeli, Luana Cortinovis, Ewa Bilska-Zając, Giorgia Angeloni

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Advanced Cotton Boll Segmentation, Detection, and Counting Using Multi-Level Thresholding Optimized with an Anchor-Free Compact Central Attention Network Model by Arathi Bairi, Uma N. Dulhare

“…There are limited techniques developed to segment, detect, and count cotton bolls precisely. …”
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Semantic Segmentation of Archaeological Features on Public Lands: Case Study of Historical Cotton Terraces within the Piedmont National Wildlife Refuge, Georgia, USA by Claudine Gravel-Miguel, Grant Snitker, Jayde N. Hirniak, Katherine Peck, Alex Fetterhoff

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PigFRIS: A Three-Stage Pipeline for Fence Occlusion Segmentation, GAN-Based Pig Face Inpainting, and Efficient Pig Face Recognition by Ruihan Ma, Seyeon Chung, Sangcheol Kim, Hyongsuk Kim

“…PigFRIS employs state-of-the-art occlusion detection with the YOLOv11 segmentation model, a GAN-based inpainting reconstruction module using AOT-GAN, and a lightweight recognition module tailored for pig face classification. …”
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Improving diagnostic precision in thyroid nodule segmentation from ultrasound images with a self-attention mechanism-based Swin U-Net model by Changan Yang, Muhammad Awais Ashraf, Mudassar Riaz, Pascal Umwanzavugaye, Kavimbi Chipusu, Kavimbi Chipusu, Hongyuan Huang, Yueqin Xu

“…BackgroundAccurate segmentation of thyroid nodules in ultrasound imaging remains a significant challenge in medical diagnostics, primarily due to edge blurring and substantial variability in nodule size. …”
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TPL-DA: A Novel Threshold-Free Pseudolabel Learning Framework for Domain Adaptive Semantic Segmentation of High-Resolution Remote Sensing Images by Yan Ren, Jie Long, Xiaowen Gao, Ming Zhang, Guoqing Liu, Nan Su

“…Semantic segmentation techniques for remote sensing scene understanding have significantly advanced, enhancing the refined Earth observation. …”
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Lightweight LDA-UNet for accurate and interpretable visualization of retinopathy of prematurity by Honghao Lu, Madhavi Devaraj

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