Search Results - (( developing function learning algorithm ) OR ( image segmentation method algorithm ))
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…Therefore, this research has developed an improved edge detection and contour segmentation algorithm that is able to correctly segment various objects from both indoor and outdoor images. …”
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2
Development of Hybrid Convolutional Neural Network and Radial Basis Function for Autism Spectrum Disorder Classification
Published 2024“…Hence, this study proposed hybrid deep learning algorithms for ASD classification. Two algorithms merged: U-net neural network and Radial Basis Function (RBF) for medical image segmentation. …”
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3
A Novel Hybrid Unet-RBF and CNN-RBF Algorithm for Autism Spectrum Disorder Classification
Published 2024“…The 2021 CDC report indicates that Autism Spectrum Disorder affects 1 in 44 children, necessitating advanced classification methods. This article proposes a hybrid deep learning approach for ASD classification, merging U-net and Radial Basis Functions for medical image segmentation and integrating Convolutional Neural Network with RBF for ASD classification. …”
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Optimizing high-density aquaculture rotifer Detection using deep learning algorithm
Published 2022“…In this paper, we present the method and performance to detect rotifer Brachionus plicatilis in 1ml sample automatically using deep learning algorithm YOLOv3. …”
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5
Deep learning convolutional neural network algorithms for the early detection and diagnosis of dental caries on periapical radiographs: a systematic review
Published 2021“…Identifying caries with a deep convolutional neural network-based detector enables the operator to distinguish changes in the location and morphological features of dental caries lesions. Deep learning algorithms have broader and more profound layers and are continually being developed, remarkably enhancing their precision in detecting and segmenting objects. …”
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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis
Published 2025“…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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Extreme Learning Machine neural networks for multi-agent system in power generation
Published 2023“…Extreme Learning Machine (ELM) is widely known as an effective learning algorithm than the conventional learning methods from the point of learning speed as well as generalization. …”
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UNSUPERVISED SEGMENTATION OF CORAL REEF IMAGES BY USING COLOR AND TEXTURE FEATURES
Published 2022“…This thesis presents new methods to automate the segmentation of underwater coral reef images based on image processing techniques with the combination of color-texture features. …”
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9
Postal address handwritten recognition using convolutional neural network / Nur Hasyimah Abd Aziz
Published 2020“…The future work may be developed by finding the new way in order the computer recognize the text without segment the image into separated character.…”
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10
Breast Ultrasound Automated ROI Segmentation with Region Growing
Published 2015“…One of the simplest methods for image segmentation that is widely implemented in medical images is the region growing method. …”
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Image segmentation based on normalised cuts with clustering algorithm
Published 2013“…With the approach applied in the normalised cuts based image segmentation, the constraint of using normalised cuts algorithm in image segmentation can be alleviated. …”
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Multiregion segmentation of mammogram images by using parametric kernel graph cut algorithm / Nurhanani Abdul Rahim, Nor Farah Nabilah Mushtafa and Nadhirah Afiqah Zailan
Published 2019“…Many methods are widely applied for image segmentation. …”
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Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation
Published 2011“…Fuzzy clustering algorithms, which fall under unsupervised machine learning, are among the most successful methods for image segmentation. …”
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14
Fuzzy modeling of brain tissues in Bayesian segmentation of brain MR images
Published 2010“…Segmentation of brain MRI is the core part in plenty of medical image processing methods. …”
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Segmenting nodules of lung tomography image with level set algorithm and neural network
Published 2019“…The aim of this research is to develop an image segmentation algorithm for nodule detection in computed tomography (CT) image. …”
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Proceedings -
16
Image enhancement and segmentation on simultaneous latent fingerprint detection
Published 2015“…Segmentation of 240 images is performed and compared with manual segmentation methods. …”
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17
Image storage and retrieval using color quantization method
Published 2005“…The image is segmented by our proposed segmentation algorithm, which uses the compact color descriptor .The result of the experiment shows that the developed segmentation algorithm produces better performances as compared with the existing segmentation algorithm. …”
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A Hybrid Active Contour and Artificial Bee Colony Algorithm for Segmenting Mixed-Meal Food Images (S/O: 13239)
Published 2020“…This method is adopted for food image segmentation, wherein the boundaries of the foods in an image are the objects of interest. …”
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Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation
Published 2008“…Fuzzy c-means (FCM) clustering algorithm has been widely used in automated image segmentation. …”
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Enhanced Clustering Algorithms For Gray-Scale Image Segmentation
Published 2012“…The clustering algorithms are widely used as an unsupervised method for image segmentation in medical diagnosis, satellite imaging and biometric systems. …”
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