Search Results - (( developing automatic optimization algorithm ) OR ( based segmentation method algorithm ))
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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 address this, we propose an efficient, modified radiomics feature processing method that integrates an optimal aerial perspective (OAP) parameter-based intensity dark channel prior (IDCP) with a 50-layer residual deep neural network (ResNet50 DNN) for autolesion segmentation (ALS-IOAP-DNN). …”
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Optimizing high-density aquaculture rotifer Detection using deep learning algorithm
Published 2022“…Second, is to develop the deep learning algorithm based on YOLOv3. Third step is to training and evaluate the model using loss function. …”
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Proceedings -
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A preliminary study on automated freshwater algae recognition and classification system / Hayat Mansoor Abdullah
Published 2012“…Based on literature review, automated identification of tropical freshwater algae is even non-existent yet, and this study is designed to fill this gap.The development process of the automated freshwater algae detection system involves with many techniques and computer methods such as image preprocessing,segmentation, feature extraction, and classification process by using ANN. …”
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Improved Genetic Algorithm Multilayer Perceptron Network For Data Classification
Published 2017“…Based on the occurrences of the best result obtained by an algorithm across different test functions; it is proven that the proposed method outperforms standard GA. …”
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Development Of Automatic Liver Segmentation Method For Three- Dimensional Computed Tomography Dataset
Published 2018“…Both methods are able to speed up the segmentation time. …”
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Monograph -
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UNSUPERVISED SEGMENTATION OF CORAL REEF IMAGES BY USING COLOR AND TEXTURE FEATURES
Published 2022“…The unsupervised segmentation of color-texture regions using J-value segmentation (JSEG) algorithm is one of the most popular and robust unsupervised segmentation algorithms. …”
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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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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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Formulation of hybrid 3D image segmentation algorithm based partial differential equation
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Proceeding Paper -
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Fuzzy modeling of brain tissues in Bayesian segmentation of brain MR images
Published 2010“…Hence involving problem specific information and expert knowledge in designing segmentation algorithms seems to be useful. A two-fold fuzzy segmentation algorithm based on Bayesian method is proposed in this paper. …”
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Conference or Workshop Item -
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Novel techniques for enhancement and segmentation of acne vulgaris lesions
Published 2013“…Methods: For the first objective, an algorithm is developed based on the theory of high dynamic range (HDR) images. …”
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Citation Index Journal -
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AUTOMATED CERVICAL CELL NUCLEI SEGMENTATION BASED ON MULTILAYER UNSUPERVISED CLUSTERING ALGORITHM AND MORPHOLOGICAL APPROACH
Published 2025“…The average segmentation score of the 917 images exceeds 90%, highlighting the method's flexibility.…”
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Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation
Published 2009“…In order to show the real time ability and robustness of proposed method for color segmentation, experimental results conducted on vision based mobile robot for navigation. …”
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Semi-automatic cortical boundary detection / Noor Elaiza Abdul Khalid.
Published 2010“…For this purpose, two algorithm are has been developed to automatically detect the OC and IC. …”
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Model-based hybrid variational level set method applied to lung cancer detection
Published 2024“…This algorithm simplifies the (Local Intensity Clustering) LIC model and devises a new energy functional based on the region-based pressure function. …”
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Segmentation of MRI brain images using statistical approaches
Published 2011“…Noise is one of the obstacles for brain MRI segmentation. The non-Local means (NL-means) algorithm is a state-of-the art neighbourhood-based noisereduction method which is time-consuming and its accuracy can be improved. …”
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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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