Segmentation of Dynamic Total-Body [18F]-FDG PET Images Using Unsupervised Clustering by Maria K. Jaakkola, Maria Rantala, Anna Jalo, Teemu Saari, Jaakko Hentilä, Jatta S. Helin, Tuuli A. Nissinen, Olli Eskola, Johan Rajander, Kirsi A. Virtanen, Jarna C. Hannukainen, Francisco López-Picón, Riku Klén

“…Clustering time activity curves of PET images have been used to separate clinically relevant areas of the brain or tumours. However, PET image segmentation in multiorgan level is much less studied due to the available total-body data being limited to animal studies. …”
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Artificial Intelligence in Fetal and Pediatric Echocardiography by Alan Wang, Tam T. Doan, Charitha Reddy, Pei-Ni Jone

“…Advances in artificial intelligence (AI), including machine learning (ML) and deep learning (DL), offer significant potential to overcome these challenges by automating image acquisition, image segmentation, CHD detection, and measurements. Despite these promising advancements, challenges such as small number of datasets, algorithm transparency, physician comfort with AI, and accessibility must be addressed to fully integrate AI into practice. …”
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Computer Vision Algorithm for the detection of fracture cracks in Oil Hardening Non-Shrinking (OHNS) die steel after machining process by Akshansh Mishra, Vijaykumar S Jatti, Nitin K Khedkar, Rahul B. Dhabale, Ashwini V Jatti

“…In the present work, U-Net convolutional neural network is implemented on Jupyter platform by using Python programming for fracture surface image segmentation in Oil Hardening Non-Shrinking (OHNS) die steel after the machining process. …”
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Autonomous Robotic Manipulation: Real-Time, Deep-Learning Approach for Grasping of Unknown Objects by Malak H. Sayour, Sharbel E. Kozhaya, Samer S. Saab

“…Our approach aims at reducing propagation errors and eliminating the need for complex hand tracking algorithm, image segmentation, or 3D reconstruction. The proposed approach is able to efficiently generate reliable multi-view object grasps regardless of the geometric complexity and physical properties of the object in question. …”
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MoNetViT: an efficient fusion of CNN and transformer technologies for visual navigation assistance with multi query attention by Liliek Triyono, Liliek Triyono, Rahmat Gernowo, Prayitno

“…Traditional CNNs handle image segmentation well, but transformers excel at capturing long-range dependencies, essential for machine vision tasks. …”
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A Framework of Vertebra Segmentation Using the Active Shape Model-Based Approach by Mohammed Benjelloun, Saïd Mahmoudi, Fabian Lecron

“…We propose a medical image segmentation approach based on the Active Shape Model theory. …”
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Object Boundary Detection Using Active Contour Model via Multiswarm PSO with Fuzzy-Rule Based Adaptation of Inertia Factor by Ajay Khunteta, D. Ghosh

“…Active contour models, colloquially known as snakes, are quite popular for several applications such as object boundary detection, image segmentation, object tracking, and classification via energy minimization. …”
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Few-Shot Contrail Segmentation in Remote Sensing Imagery With Loss Function in Hough Space by Junzi Sun, Esther Roosenbrand

“…This transformation improves performance over generic image segmentation loss functions. The openly shared few-shot learning library, contrail-seg, has demonstrated that few-shot learning can be effectively applied to contrail segmentation with the new loss function.…”
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Design and Implementation of Brain Tumor Segmentation and Detection Using a Novel Woelfel Filter and Morphological Segmentation by M Venu Gopalachari, Morarjee Kolla, Rupesh Kumar Mishra, Zarin Tasneem

“…Detection techniques like image segmentation are heavily reliant on the segmented image’s resolution. …”
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Transmission Line Condition Monitoring Method Based on Binocular Vision and Edge Computing for Line Changing Robot by Zheng Lu, Jiazhen Duan, Xiaoqiang Chen, Yang Chen

“…Aiming to realize fast and efficient transmission cable state analysis with the help of a binocular vision tool on a loop dismantling robot, this paper proposes a transmission cable state recognition method combining motion control and image segmentation technology. In this method, the fuzzy PID control method is adopted to ensure that the wire removal robot can realize high-precision and rapid response control and effectively improve the collection quality of the cable image sample set. …”
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Identifying industrial buildings as a spatial resource for sustainable urban regeneration in high-density post-industrial metropolitan in Asia by Miao Sun, Tan Qin, Yuanxiao Kuang, Jianchang Lv

“…It extracts vector footprints of buildings from aerial imagery through image segmentation, establishes a feature engineering model comprising 11 distinct indicators, and introduces a Random Forest model to enhance the analysis. …”
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A weak edge estimation based multi-task neural network for OCT segmentation. by Fan Yang, Pu Chen, Shiqi Lin, Tianming Zhan, Xunning Hong, Yunjie Chen

“…With the development of deep learning, deep learning-based methods are becoming more popular for fundus OCT image segmentation. Yet, these methods still encounter two primary challenges. …”
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Ear Biometric Identification based on Gabor Filters using Backpropagation Neural Networks by Ivano Kumaran, Muchtar Ali Setyo Yudono, Alun Sujjada

“…The preprocessing steps include resizing the images, converting them to grayscale, and applying Gaussian filters. Image segmentation is performed using Canny edge detection, followed by morphological operations such as dilation and hole filling. …”
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Accurate Recognition and Simulation of 3D Visual Image of Aerobics Movement by Wenhua Fan, Hyun Joo Min

“…The model is improved on the basis of the traditional model and unifies the process of aerobics 3D visual image segmentation, target feature extraction, and target recognition. …”
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Experimental assessment of damage and microplastic release during cyclic loading of clear aligners. by Claudia Barile, Claudia Cianci, Vimalathithan Paramsamy Kannan, Giovanni Pappalettera, Carmine Pappalettere, Caterina Casavola, Michele Laurenziello, Domenico Ciavarella

“…A dimensional analysis based on k-means image segmentation and edge detection algorithm is developed to analyse the MPs. …”
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Effective First-Break Picking of Seismic Data Using Geometric Learning Methods by Zhongyang Wen, Jinwen Ma

“…Specifically, in the case of unsupervised learning, we design an effective curve evolving algorithm according to the active contour(AC) image segmentation model, in which the length of the target curve and the fitting region energy are minimized together. …”
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Multiple Scaling Based EfficientNet Modelling for Liver Tumor Classification on CT Images by Bilga Jacob, R. S. Vinod Kumar, S. S. Kumar

“…Recent, deep Convolutional Neural Network (CNN) research has produced amazing improvements in image segmentation and classification. The same issue of diagnosing liver nodules in computed tomography (CT) scans is addressed in this research by introducing a novel Computer-Aided Detection (CAD) system that makes use of an Efficient Network (EfficientNet) image classification algorithm. …”
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Image Recognition Method of Agricultural Pests Based on Multisensor Image Fusion Technology by Xianfeng Zeng, Changjiang Huang, Liuchun Zhan

“…In terms of image recognition, the use of image denoising methods based on median filtering, image preprocessing methods based on the maximum between-class error method (Otsu), image segmentation methods based on super green features, and feature extraction methods based on multiparameter features and based on the one-to-one elimination strategy and the M-SVM multiclass recognition algorithm fused with the kernel function, it realizes the identification and detection of six soybean leaf borers. …”
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Lightweight Multi-Scale Network for Segmentation of Riverbank Sand Mining Area in Satellite Images by Hongyang Zhang, Shuo Liu, Huamei Liu

“…The rapid identification of riverbank sand mining areas from satellite images is extremely important for ecological protection and shipping management. Image segmentation methods based on AI technology are gradually becoming popular in academia and industry. …”
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Towards Enhancement of Performance of K-Means Clustering Using Nature-Inspired Optimization Algorithms by Simon Fong, Suash Deb, Xin-She Yang, Yan Zhuang

“…In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario.…”
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