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444 articles for “segmentations”
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CNN-Based Wound Segmentation: A Review of Models and Performance Evaluation
Abstract: Deep learning, particularly convolutional neural networks (CNNs), has altered medical image processing by automating and precisely segmenting complex medical pictures. Wound segmentation, a critical application in automated wound assessment, is essential for wound size estimation, classification, and healing progress monitoring. This study presents a comprehensive review of CNN-based wound segmentation models, focusing on their architectures, methodologies, and performance on diverse datasets. Four deep learning models, including two U-Net variants (5-layer …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 33–46 Read article
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A Review on Image Segmentation with Its Application
Abstract: ‘Image Segmentation’ is the most basic capacities in picture examination and preparing. In a broad sense, division results influence all the ensuing procedures of picture examination, for example, object representation and portrayal, component estimation, and even the accompanying larger amount assignments, like object arrangement. Henceforth, image segmentation is the most fundamental and vital procedure for encouraging the outline, portrayal, and representation of the locales of enthusiasm for any picture. Image …
Published in Journal of Open Source Developments · Vol. 2, Issue 2, 2015 · pp. 21–29 Read article
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Region Segmentation and Annotation with Vehicle Detection Validation Application in Airborne Images
Abstract: In this work, the authors propose an automatic image segmentation and annotation system for airborne images. Initial region segmentation using existing region segmentation methods is applied to airborne images first. To deal with over-segmentation on the initial region segmentation results, the authors performed graph-based region merging by constructing an undirected-graph based on 8-connected local neighborhood. For each region, the authors extracted low-level features and used the Support Vector Machine (SVM) …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 1, 2014 · pp. 9–19 Read article
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Assessment of Metal Concentrations in Water from the Downstream Segment of New Calabar River, Port Harcourt Segment of New Calabar River, Port Harcourt
Abstract: The downstream segment of the New Calabar River, Port Harcourt has been a major source of water and sea foods for the inhabitants. The concentration of heavy and trace metals such as Cadmium (Cd), Lead (Pb), Mercury (Hg), Copper (Cu) and Iron (Fe) in water were investigated between January – December, 2016 using Atomic Absorption Spectrophotometer (AAS). The results showed that station 2 had the highest concentration of the metals …
Published in Research & Reviews : Journal of Ecology · Vol. 9, Issue 1, 2020 Read article
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Advancing Brain Tumor MRI Segmentation
Abstract: Segmentation of brain tumors in MRI scans is an integral part of neuroimaging carried out for diagnostic and therapeutic interventions. Given that manual segmentation is cumbersome and highly variable, there arises a need for automated, more precise segmentation solutions. This project, ‘Machine Learning and Deep Neural Networks to Advance Brain Tumor MRI Segmentation’ will develop a better, efficient, and accurate segmentation model to help clinicians identify brain tumors with greater …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 2, 2025 · pp. 28–33 Read article
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A Comparative Study on Image Segmentation using Maximal Similarity Region Merging
Abstract: Segmentation is a low level process concerned with images partitioning through defining discontinuity or similarity or equivalently, through finding boundaries or edges. Image segmentation is a mechanism used for an image divide into numerous segments. The main objective is to create the image meaningful and more simple, so as to modification the an image optimization into the something that is additional important and easier to study various approaches of image …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 2, Issue 3, 2015 · pp. 1–8 Read article
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A Survey based on Image Segmentation for various Approaches
Abstract: The procedure of image segmentation is the system by means of which a given picture is segmented into a few sections with the end goal to examine into more reasonable shape. The image segmentation has incredible significance in the region of image processing. There are certain elements that influence the procedure of picture segmentation like the intensity of picture to be segmented, color, type and the commotion present in the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 3, 2018 · pp. 1–6 Read article
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A Split and Merge UNet: A Deep Learning Assisted UNet Model to Segment Corpus Callosum of Brain for Automatic Autism Detection
Abstract: In recent years, deep learning techniques have shown remarkable performance in various image analysis applications, particularly in the domain of medical image processing. Among these, image segmentation plays a critical role, as it helps in isolating and analyzing specific regions within medical images. The proposed study focuses on segmenting the corpus callosum, a vital structure in the human brain, using a novel optimization technique known as the Split and Merge …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Colour Based Segmentation of a Landsat Image Using K-Means Clustering Algorithm
Abstract: AbstractImage segmentation is one of the typical vintage subjects in image processing and it acts as a bulls-eye of the image processing technique. By definition, image segmentation means identifying the similar regions in the image; or in other words, identifying the homogenous pixels in the image and grouping all these pixels based on the homogeneity condition considered. This homogeneity condition can be like, colour, texture, size, compactness etc. It is …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 4, Issue 3, 2017 · pp. 31–38 Read article
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Deep Learning for Grape Cluster Segmentation
Abstract: Grape cluster identification and its segmentation for the purpose of vineyard total weight prediction tasks indicate the need for more accurate segmentation atomization. The Grape Cluster Segmentation challenge is supplied as an answer the usage of deep neural community fashions including YOLO v3, Mask RCNN, and U-net. In the sense of a modified U-net model for segmenting grapes using training and testing strategies, this contribution contributes to the validation of …
Published in Recent Trends in Programming languages · Vol. 8, Issue 2, 2021 · pp. 23–32 Read article
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Segmentation Methods for Images: A Systematic Review
Abstract: Image segmentation is the initial operation in image processing and computer vision to extract a region of interest from a still image or a sequence of images (video). Segmentation is the key operation to perform a number of applications today. Different supervised and unsupervised evaluation methods have been used for segmentation for numerous applications, but still it is a challenging task to identify which method is more accurate. This paper …
Published in Journal of Remote Sensing & GIS · Vol. 4, Issue 3, 2013 · pp. 61–67 Read article
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Image Segmentation based on Region Merging using Breadth-First Search
Abstract: This paper proposed a new method for image segmentation based on region merging using breadth-first search (BFS). The image can be partitioned into multiple segments so that meaningful information is extracted out and then image is analyzed easily. In the proposed method, first the oversegmented image is obtained by applying a standard watershed transformation on original image. Then BFS is executed on the oversegmented image to obtain a segmented image. …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 1, 2014 · pp. 20–25 Read article
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Segmentation Methods Applied on MR Medical Application
Abstract: AbstractImage segmentation techniques as applied in MRI of human brain are developing by leaps and bounds. The human brain is the most imaging design of the nature. Cancer and neurological problems are resolved using MR of the brain. The automatic diagnostic system starts with medical imaging, segmentation and analysis of the findings and then the final decisions which are further used to treat the patient. In the real world certain …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 3, 2016 · pp. 30–38 Read article
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A Review on MR Brain Image Segmentation Based on Different Techniques
Abstract: In past few years, the growth in Magnetic Resonance Imaging (MRI) provided a new way to detect and diagnose the brain related problems such as Alzheimer, schizophrenia and brain tumor. Many supervised and unsupervised techniques are available for image segmentation. In medical field supervised and unsupervised segmentation both are available but unsupervised is in more demand then supervised because it requires external assistance. Whereas unsupervised segmentation reflects better results. In …
Published in Journal of Operating Systems Development & Trends · Vol. 2, Issue 2, 2015 · pp. 9–14 Read article
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A Novel Approach of Image Restoration Based on Segmentation and Fuzzy Clustering
Abstract: Image restoration is the process of restoring or deblurring an image which had been undergone certain degradations. In this paper, we proposed a method for image restoration based on segmentation and fuzzy clustering. This method consider the similar image pair in which there is a clear part in one image corresponding to degraded one in another. This proposed method firstly partition the image into specified segments and then use fuzzy …
Published in Recent Trends in Programming languages · Vol. 1, Issue 2, 2014 · pp. 1–6 Read article
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A GIS Based Tool to Digitize Polygon and Line Segments of a Black and White Map
Abstract: In this paper a GIS based tool has been proposed to digitize polygon and line objects throughefficient usage of RGB values of the segments of raster maps. For digitization of polygon,initially a closed loop is drawn inside the polygon segment. Beginning from the initial point ofthe closed loop, eight connected pixels calculation is incorporated to obtain the pointsexisting in between the loop and the actual boundary. The points which exist …
Published in Journal of Remote Sensing & GIS · Vol. 7, Issue 1, 2016 · pp. 27–41 Read article
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Refining Retinal Layer Segmentation in OCT Imaging with Advanced Techniques and Clinical Applications
Abstract: Segmenting retinal layers from Optical Coherence Tomography (OCT) pictures entails locating and separating different retinal layers to offer comprehensive anatomical and pathological information. Age-related macular degeneration, diabetic retinopathy, and glaucoma are among the retinal illnesses for which this procedure is crucial for diagnosis and follow-up. By utilizing preprocessing techniques to improve image quality and applying advanced algorithms—such as intensity-based, gradient-based, and texture-based methods—alongside deep learning approaches, clinicians can accurately measure …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 01–06 Read article
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Automated Microstructure Classification with Class-Specific Segmentation for Titanium Based Composite Materials
Abstract: In engineering, characterisation of microstructure is required to determine and forecast behaviour of titanium alloys. Our proposal in this work has been a deep-learning-based framework in the automatic classification and segmentation of Titanium Based Composite Material. The framework then uses EfficientNetB0 backbone, where we have chosen the backbone to scale the performance of classification and the computational efficiency with the assistance of the transfer learning and the compound scaling. In …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 424–433 Read article
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Text Line Segmentation for Kannada Language Using Enhanced Horizantol Projection Profile Method
Abstract: Handwritten character image is taken as dataset for this method. Segmentation is crucial in the Human Character Recognition System for extracting text lines, words, and characters from handwritten Kannada documents. In the proposed system, segmenting text lines, word, characters are done based on enhanced horizantol projection profile approach. The algorithm will be used for finding the height and width of the entire handwritten word The horizontal projection profile approach is …
Published in Journal of Electronic Design Technology · Vol. 14, Issue 2, 2023 · pp. 1–8 Read article
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Tweet Segmentation for Named Entity Recognition
Abstract: AbstractTwitter is having lots of users to allocate and distribute a large amount of recent information, various submission in Information Retrieval-IR and Natural Language Processing-NLP undergo harshly through the deafening and tinny kind of tweets. We recommend tweet segmentation framework in a group, called HybridSeg. By dividing tweets with significant segments, the background information is conserved and simply extract with the downstream applications. HybridSeg search the best segmentation of a …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 3, Issue 3, 2016 · pp. 22–25 Read article