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  1. 1
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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  2. 2
    Machine learning approach for automated optical inspection of electronic components

    Machine learning approach for automated optical inspection of electronic components by Lim, Siew Kee

    Published 2019
    “…The factor that affecting the confidence level of the supervised machine learning algorithm is discussed. …”
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    Final Year Project / Dissertation / Thesis
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  3. 3
    Automated visual defect detection using deep learning

    Automated visual defect detection using deep learning by Loh, Xiao

    Published 2022
    “…Artificial intelligence visual inspection is a technique which utilises computer vision and deep learning technology to mechanically “see” a product and determine whether it has defects, without any human involvement. …”
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  4. 4
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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    Book
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  5. 5
    Development of seven segment display recognition using TensorFlow on Raspberry Pi

    Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

    Published 2022
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    Proceeding Paper
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  6. 6
    Defect green coffee bean detection using image recognition and supervised learning

    Defect green coffee bean detection using image recognition and supervised learning by Shafian Izan Sofian

    Published 2022
    “…Normally, the evaluation that is carried out in determining the quality of green coffee is by visual inspection where it has limitations, and it is prone to error. …”
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    Academic Exercise
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  7. 7
    Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah

    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
    “…In general, this thesis introduces an automated machine learning algorithm for detecting diabetic retinopathy (DR) in fundus images. …”
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  8. 8
    An adaptive HMM based approach for improving e-Learning methods

    An adaptive HMM based approach for improving e-Learning methods by Deeb B., Hassan Z., Beseiso M.

    Published 2023
    “…Maladaptive e-Learning systems cannot impart quality content for each student as the users observe the information based on their exclusive learning traits. …”
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  9. 9
    Defects identification on semiconductor wafer for yield improvement using machine learning / Pedram Tabatabaeemoshiri

    Defects identification on semiconductor wafer for yield improvement using machine learning / Pedram Tabatabaeemoshiri by Pedram , Tabatabaeemoshiri

    Published 2025
    “…This work presents a novel graph-based semi-supervised learning (GSSL) algorithm designed for wafer defect detection. …”
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  10. 10
    Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir

    Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir by Amir, Nur Hazirah

    Published 2019
    “…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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  11. 11
    Agarwood oil grade clustering of aquilaria malaccensis species using Extraction by GC-MS analysis: Efficient KNN algorithm based on patterns visualization of two-dimensional graph

    Agarwood oil grade clustering of aquilaria malaccensis species using Extraction by GC-MS analysis: Efficient KNN algorithm based on patterns visualization of two-dimensional graph by Siti Mariatul Hazwa, Mohd Huzir, Anis Hazirah ‘Izzati H., Al-Hadi, Amir Hussairi, Zaidi, Nurlaila F., Ismail, Zakiah, Mohd Yusoff, Saiful Nizam, Tajuddin, Mohd Nasir, Taib

    Published 2024
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  12. 12
    Diabetic retinopathy pathological signs detection using image enhancement technique and deep learning / Abdul Hafiz Abu Samah …[et al.]

    Diabetic retinopathy pathological signs detection using image enhancement technique and deep learning / Abdul Hafiz Abu Samah …[et al.] by Abu Samah, Abdul Hafiz, Ahmad, Fadzil, Osman, Muhammad Khusairi, Md Tahir, Noritawati, Idris, Mohaiyedin, Abd. Aziz, Nor Azimah

    Published 2021
    “…It also involves an image pre-processing enhancement technique to support accuracy on deep learning for DR classification. For the image enhancement process, high-pass filter, histogram equalization and de-haze algorithm are applied to improve the visual quality of fundus images. …”
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  13. 13
    Fog-cloud scheduling simulator for reinforcement learning algorithms

    Fog-cloud scheduling simulator for reinforcement learning algorithms by Al-Hashimi, Mustafa Ahmed Adnan, Rahiman, Amir Rizaan, Muhammed, Abdullah, Hamid, Nor Asilah Wati

    Published 2023
    “…Therefore, supplying optimized scheduling algorithms to provide satisfactory quality service for the node’s task execution and processing becomes demanding. …”
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  14. 14
    Automatic Grading System Of Incoming Raw Unclean Edible Bird Nest Using Deep Learning Model

    Automatic Grading System Of Incoming Raw Unclean Edible Bird Nest Using Deep Learning Model by Khor, Khye Jim

    Published 2021
    “…Therefore, a deep learning model with the self-learning ability on the feature extraction process and low human intervention was developed to solve the drawbacks of the human visual system and conventional algorithms. …”
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    Monograph
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  15. 15
    Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques

    Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques by Arif Z.H., Mahmoud M.A., Abdulkareem K.H., Mohammed M.A., Al-Mhiqani M.N., Mutlag A.A., Dama�evi?ius R.

    Published 2023
    Review
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  16. 16
    Anomaly detection for vision-based inspection

    Anomaly detection for vision-based inspection by Chew, Yan Zhe

    Published 2022
    “…There are two approaches to visual inspection: the conventional approach which uses image processing techniques and the modern AI-based approach through deep learning. …”
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  17. 17
    Lighting enhancement of underwater image using coronavirus herd immunity optimizer

    Lighting enhancement of underwater image using coronavirus herd immunity optimizer by Alyasseri Z.A.A., Ghalib R., Jamil N., Mohammed H.J., Ali N., Ali N.S., Al-Wesabi F.N., Assiri M.

    Published 2025
    “…Therefore, many researchers have been attracted to developing diverse computer vision-based methods to improve the quality of underwater images, such as restoration, enhancement, and deep-learning techniques to restore and enhance degraded underwater images. …”
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  18. 18
    Low-light image analysis and contrast enhancement using gaussian process / Loh Yuen Peng

    Low-light image analysis and contrast enhancement using gaussian process / Loh Yuen Peng by Loh , Yuen Peng

    Published 2018
    “…Experimental results show that the proposed method outperforms the state-of-the-art in the common visual quality measure, the peak signalto- noise ratio (PSNR) by 1.17dB. …”
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  19. 19
    A review of wave-net identical learning & filling-in in a decomposition space of (JPG-JPEG) sampled images

    A review of wave-net identical learning & filling-in in a decomposition space of (JPG-JPEG) sampled images by Al-Azzawi, Alaa Khamees, Saripan, M. Iqbal, Jantan, Adznan, O. K. Rahmat, Rahmita Wirza

    Published 2010
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  20. 20
    Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm

    Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm by Shah, Abdul Salam, Mohamad Nasir, Haidawati, Fayaz, Muhammad, Lajis, Adidah, Ullah, Israr, Shah, Asadullah

    Published 2020
    “…For the comfort index (thermal, visual, and air quality), we have used three parameters, i.e., Temperature (◦F), illumination (lx), and CO2 (ppm). …”
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