Search Results - (( java implementation learning algorithm ) OR ( waste detection learning algorithm ))
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1
Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
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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Performance Review of Modern AI Algorithms Utilized for Medical Waste Sorting Works
Published 2025Subjects:Conference paper -
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RGB and RGNIR image dataset for machine learning in plastic waste detection
Published 2025“…The proposed dataset offers a unique resource for researchers to train machine learning models for plastic waste detection. While there are existing datasets on plastic waste, the proposed dataset aims to set itself apart by offering a more comprehensive dataset with unique spectral information in the near-infrared region. …”
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4
An Embedded Machine Learning-Based Spoiled Leftover Food Detection Device for Multiclass Classification
Published 2024“…Several studies have examined the factors influencing food waste behaviour and management. This work was motivated by the lack of previous research on machine learning and electronic noses to detect contamination from leftover cooked food. …”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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8
A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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9
IoT-Enabled Waste Tracking and Recycling Optimization : Enhancing Sustainable Waste Management
Published 2025“…A Convolutional Neural Network (CNN) trained on a dataset of aluminium cans and plastic bottles is deployed for waste identification. Real-time monitoring is enabled by IoT sensors and machine vision algorithms, facilitating precise detection of waste levels and material types. …”
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10
Automation of plastic waste sorting through robotic technology
Published 2025“…The methodology involved fabricating a conveyor belt system, designing a slider mechanism to extend the Delta X robotic arm’s reach and equipping the robot with a vacuum gripper for pick-and-place operations. A YOLOv8 deep learning model, trained on a custom dataset of waste images, was integrated with the ByteTrack algorithm to provide real-time object detection and tracking. …”
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Final Year Project / Dissertation / Thesis -
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Diabetic retinopathy pathological signs detection using image enhancement technique and deep learning / Abdul Hafiz Abu Samah …[et al.]
Published 2021“…Therefore, it is time-wasting and risky for humans to make mistake. In general, this paper introduces an automated machine learning algorithm for detecting diabetic retinopathy (DR) in fundus images. …”
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An approach of classifying waste using transfer learning method
Published 2021“…We then distinguished between specific transfer learning algorithms for our project: Xception, DenseNet121, Resnet-50, MobilenetV2, and EffiecienNetB7. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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14
Smart waste management system with IoT monitoring
Published 2023“…Through advanced data analytics and machine learning algorithms, the platform predicts waste accumulation patterns, optimizes collection routes, schedules pickups based on fill-level data, and detects any abnormal conditions. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Talkout : Protecting mental health application with a lightweight message encryption
Published 2022“…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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Academic Exercise -
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A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee
Published 2023“…Any resampling algorithm is not a necessity in the case of this proposed algorithm. …”
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18
Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
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Conference or Workshop Item -
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Automated density and growth estimation in precision aquaculture systems for prawn cultivation using computer vision techniques
Published 2024“…To address these challenges, this project proposes an innovative solution that leverages computer vision and machine learning techniques. By employing the state-of-the-art You Only Look Once (YOLO) v7 object detection algorithm, the project aims to develop a system capable of accurately detecting and classifying prawns based on their growth stages. …”
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Final Year Project / Dissertation / Thesis -
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A malware analysis and detection system for mobile devices / Ali Feizollah
Published 2017“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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