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  1. 1
    An internet of things based for smart recycle waste classification / Akmal Md Nasir

    An internet of things based for smart recycle waste classification / Akmal Md Nasir by Md Nasir, Akmal

    Published 2023
    “…To accurately categorise waste into the categories of metal, paper, plastic, and maybe other waste types, the system uses an image classification model based on the ResNet algorithm. …”
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    Thesis
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  2. 2
    Waste management using machine learning and deep learning algorithms

    Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

    Published 2020
    “…So, we are proposing an automated waste classification problem utilizing Machine Learning and Deep Learning algorithms. …”
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  3. 3
    ESS-IoT: The Smart Waste Management System for General Household

    ESS-IoT: The Smart Waste Management System for General Household by Wong S.Y., Han H., Cheng K.M., Koo A.C., Yussof S.

    Published 2024
    “…On the other hand, the waste classification is implemented using two classification algorithms: Random Forest (RF) prediction model and Convolutional Neural Network (CNN) prediction model. …”
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  4. 4
    Real-time intelligent recycle waste detection and classification using you only look once version 5 / Aiman Syafwan Amran

    Real-time intelligent recycle waste detection and classification using you only look once version 5 / Aiman Syafwan Amran by Amran, Aiman Syafwan

    Published 2023
    “…Because of that, this project aims to detect and classify a typed of recycled waste such paper, plastic and metal. It uses YOLOv5 object detection and classification algorithm. …”
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  5. 5
    Recyclable waste classification using YOLO-based Convolutional Neural Network (CNN) / Shaharil Armin Sharizal

    Recyclable waste classification using YOLO-based Convolutional Neural Network (CNN) / Shaharil Armin Sharizal by Sharizal, Shaharil Armin

    Published 2025
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  6. 6
    Classification model for water quality using machine learning techniques

    Classification model for water quality using machine learning techniques by Azilawati, Rozaimee, Azrul Amri, Jamal, Azwa, Abdul Aziz

    Published 2015
    “…In assessing the result, the Lazy model using K Star algorithm was the best classification model among the five models had the most outstanding accuracy of 86.67%. …”
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  7. 7
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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  8. 8
    Performance Review of Modern AI Algorithms Utilized for Medical Waste Sorting Works

    Performance Review of Modern AI Algorithms Utilized for Medical Waste Sorting Works by Moktar M.H., Hajjaj S., Mohamed H., Weng L.Y.

    Published 2025
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  9. 9
    AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING

    AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING by SALLEH AL-HUMAIKANI, MOHAMMED ABDULQAWI

    Published 2021
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  10. 10
    Medical Waste Detection and Classification Through YOLO Algorithms

    Medical Waste Detection and Classification Through YOLO Algorithms by Moktar M.H.B., Hajjaj S.S.H., Mohamed H.

    Published 2025
    Conference paper
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  11. 11
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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  12. 12
    IoT-Enabled Waste Tracking and Recycling Optimization : Enhancing Sustainable Waste Management

    IoT-Enabled Waste Tracking and Recycling Optimization : Enhancing Sustainable Waste Management by Eugine Teh, Yin Jie, Chee Soon, Chong, Rozaimi, Ghazali, Hazriq Izzuan, Jaafar, Muhamad Fadli, Ghani, Howe Cheng, Teng, Nur Farhanah, Zulkipli, Siaw Hong, Liew

    Published 2025
    “…Advanced data preprocessing, such as augmentation and normalization, ensures robust model training, while optimized algorithms guide waste sorting based on classification results. …”
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    Proceeding
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  13. 13
    Mixed waste classification based on vision inspection / Hassan Mehmood Khan

    Mixed waste classification based on vision inspection / Hassan Mehmood Khan by Hassan Mehmood , Khan

    Published 2022
    “…Classification of dry waste garbage is crucial since incorrect labelling of dry waste types may contribute huge loss to waste industry. …”
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  14. 14
    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter

    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

    Published 2019
    “…It does not consider the LACE algorithm implemented in huge number of server in one Cloud datacenter. …”
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  15. 15
    Fault classification in transmission line using single layer feed-forward network trained by extreme learning machine / Muhamad Azfar Abd Ghafar

    Fault classification in transmission line using single layer feed-forward network trained by extreme learning machine / Muhamad Azfar Abd Ghafar by Abd Ghafar, Muhamad Azfar

    Published 2015
    “…This paper present a study of fault classification in transmission line with a combination of wavelet transform (WT) and single layer feed-forward network (SLFN) trained by Extreme Learning Machine (ELM) algorithm. …”
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  16. 16
    Fault classification in transmission line using single layer feed-forward network trained by extreme learning machine / Muhamad Azfar Abd Ghafar

    Fault classification in transmission line using single layer feed-forward network trained by extreme learning machine / Muhamad Azfar Abd Ghafar by Abd Ghafar, Muhamad Azfar

    Published 2015
    “…This paper present a study of fault classification in transmission line with a combination of wavelet transform (WT) and single layer feed-forward network (SLFN) trained by Extreme Learning Machine (ELM) algorithm. …”
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  17. 17
    Route Optimization System

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…Using that process, we have settled on Java as our development platform as we found it able to both implement DA and the GIS component (map display and manipulation). …”
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    Final Year Project
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  18. 18
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  19. 19
    The classification of FTIR plastic bag spectra via label spreading and stacking

    The classification of FTIR plastic bag spectra via label spreading and stacking by Almanifi, Omair Rashed Abdulwareth, Ng, Jee Kwan, Anwar P. P., Abdul Majeed

    Published 2021
    “…Four pipelines were investigated, consisting of two machine learning algorithms, a stacked model that stacks the KNN, SVM and RF algorithms together, and Label spreading, as well as two different dimensionality reduction methods namely; SVD and UMAP. …”
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  20. 20
    An approach for cross-site scripting detection and removal based on genetic algorithms.

    An approach for cross-site scripting detection and removal based on genetic algorithms. by Hydara, Isatou, Md Sultan, Abu Bakar, Zulzalil, Hazura, Admodisastro, Novia

    Published 2014
    “…The proposed approach is, so far, only implemented and validated on Java-based Web applications, although it can be implemented in other programming languages with slight modifications. …”
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    Conference or Workshop Item
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