Search Results - (( java segmentation using algorithm ) OR ( waste detection efficient algorithm ))
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1
Image clustering comparison of two color segmentation techniques
Published 2010“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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Thesis -
2
Automatic Number Plate Recognition on android platform: With some Java code excerpts
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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3
Development of seven segment display recognition using TensorFlow on Raspberry Pi
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4
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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5
Design of smart waste bin and prediction algorithm for waste management in household area
Published 2018“…This project has proposed Artificial Neural Network (ANN) based prediction algorithm that can forecast Solid Waste Generation (SWG) based on household size factor. …”
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6
RGB and RGNIR image dataset for machine learning in plastic waste detection
Published 2025“…In total, there are 1,344 plastic waste objects that have been annotated. The proposed dataset offers a unique resource for researchers to train machine learning models for plastic waste detection. …”
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7
Automation of plastic waste sorting through robotic technology
Published 2025“…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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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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10
Fault detection and diagnosis for gas density monitoring using multivariate statistical process control
Published 2011“…Therefore, an efficient fault detection and diagnosis algorithm needs to be developed to detect faults that are present in a process and pinpoint the cause of these detected faults. …”
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11
Automated density and growth estimation in precision aquaculture systems for prawn cultivation using computer vision techniques
Published 2024“…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 -
12
Analysis of the effectiveness of natural treatments for preserving apricots and the YOLOv7 application for early damage detection
Published 2025“…Therefore, this study is expected to reduce the workload in post-harvest fruit processing and help in the rapid identification and detection of damaged fruits based on smart detection algorithms, thus improving sorting efficiency and reducing both waste and economic losses, which enhances smart agriculture technologies.…”
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13
Energy-Aware Clustering Routing for Mobile Ad-Hoc Sensor Networks (MASNETS)
Published 2020“…Keywords: MASNETs, energy efficiency, clustering…”
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14
Evolutionary cost-cognizant regression test case prioritization for object-oriented programs
Published 2019“…Afterward evolutionary algorithm (EA) was employed to prioritize test cases based on the rate severity of fault detection per unit test cost. …”
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15
A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee
Published 2023“…The proposed deep learning model renders faster without the use of SMOTE. Any resampling algorithm is not a necessity in the case of this proposed algorithm. …”
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16
Improvement of xylanase production by recombinant Escherichia coli DH5α using fed-batch fermentation
Published 2011“…These results indicate that efficient process control strategy is important for the improvement of xylanase production by E. coli DH5α…”
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