Search Results - (( image classification problems algorithm ) OR ( evolution classification based algorithm ))

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  1. 1

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…In order to improve recognition of high interclass similarity activities, One-Versus- All (OVA) binarization strategy is introduced by transforming original multi-class classification problems into a series of two-class classification problems. …”
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    Thesis
  2. 2

    An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images by Ibrahim, I., Ibrahim, Z., Khalil, K., Mokji, M.M., Abu Bakar, S.A.R.S., Mokhtar, N., Ahmad, W.K.W.

    Published 2012
    “…The defect classification algorithm is improved by incorporating proper image registration and thresholding techniques to solve the alignment and uneven illumination problem. …”
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    Article
  3. 3

    Supervised ANN classification for engineering machined textures based on enhanced features extraction and reduction scheme by Ashour, Mohammed Waleed, Khalid, Fatimah, Al-Obaydee, Mohammed

    Published 2013
    “…Some of the main problems of image classification are the poor features that does not precisely represent an image, and the large dimensionality of data input passed to classifiers. …”
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  4. 4

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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    Thesis
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    Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

    Published 2019
    “…The first algorithm locates interest points in food images using an MSER. …”
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    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…In general, image segmentation isolates an object from the images, feature extraction creates features for classification phase while object classification categorizes objects into the correct groups. …”
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    Thesis
  10. 10

    UNSUPERVISED SEGMENTATION OF CORAL REEF IMAGES BY USING COLOR AND TEXTURE FEATURES by MOHAMMAD SAMEER ALOUN

    Published 2022
    “…This thesis proposed a modified JSEG algorithm to solve the problem of over segmentation when applying it to underwater coral reef images.…”
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    Thesis
  11. 11

    Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy by Al-Dabbagh, Rawaa Dawoud, Neri, Ferrante, Idris, Norisma, Baba, Mohd Sapiyan

    Published 2018
    “…These fine-tuning techniques continue to be the object of ongoing research. Differential evolution (DE) is a simple yet powerful population-based metaheuristic. …”
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    Article
  12. 12

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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    Thesis
  13. 13

    Image authentication using Zernike moment watermarking by Shojanazeri, Hamid

    Published 2013
    “…The adding or replacing a portion of the image is regarded as malicious attacks and rejected by this algorithm. …”
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    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

    Published 2017
    “…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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    Article
  17. 17

    Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah by Abu Samah, Abdul Hafiz

    Published 2021
    “…For the image enhancement process, this thesis has proposed high-pass filter combined with histogram equalization and de-haze algorithm respectively to improve the visual quality of fundus images. …”
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    Thesis
  18. 18

    Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari by Sha’ari, Nor Silawati

    Published 2018
    “…NN such as Artificial Neural Network (ANN) and K-Nearest Neighbor (KNN) is trained in developing a classification system for agriculture purpose. ANN and KNN is applied to solve the problems in image analysis, pattern recognition and classification. …”
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    Student Project
  19. 19

    Recent Advances in Classification of Brain Tumor from MR Images – State of the Art Review from 2017 to 2021 by Ghazanfar, Latif, Faisal Yousif, Al Anezi, Dayang Nurfatimah, Awang Iskandar, Abul, Bashar, Jaafar, Alghazo

    Published 2022
    “…The complex nature of the brain tissue makes the problem of locating, segmenting, and ultimately classifying Magnetic Resonance (MR) images a complex problem. …”
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    Article
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    Decision tree as knowledge management tool in image classification by Kusrini, , Harjoko, Agus

    Published 2008
    “…Expert System has been grown so fast as a science that study how to make computer capable of solving problems that typically can only be solved by expert.It has been realized that the biggest challenge of developing expert system is the process include expert’s knowledge into the system.This research tries to model expert’s knowledge management using case based reasoning method.The knowledge itself is not inputted directly by the expert, but rather the system will learn the knowledge from what the expert did to the previous cases.This research takes image classification as the problem to be solved.As the knowledge development technique, we build decision tree by using C4.5 algorithm.Variables used for building the decision tree are the image visual features.…”
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    Conference or Workshop Item