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PCB defect detection system using run-length encoding
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Student Project -
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks
Published 2023“…The CICIDS2017 dataset includes benign and up-to-date examples of typical attacks, closely matching real-world data of Packet Capture. The four models are tested and assessed using Confusion Metrix against four commonly used criteria: accuracy, precision, recall, and F-measure. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks
Published 2023“…The CICIDS2017 dataset includes benign and up-to-date examples of typical attacks, closely matching real-world data of Packet Capture. The four models are tested and assessed using Confusion Metrix against four commonly used criteria: accuracy, precision, recall, and F-measure. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks
Published 2023“…The CICIDS2017 dataset includes benign and up-to-date examples of typical attacks, closely matching real-world data of Packet Capture. The four models are tested and assessed using Confusion Metrix against four commonly used criteria: accuracy, precision, recall, and F-measure. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks
Published 2023“…The CICIDS2017 dataset includes benign and up-to-date examples of typical attacks, closely matching real-world data of Packet Capture. The four models are tested and assessed using Confusion Metrix against four commonly used criteria: accuracy, precision, recall, and F-measure. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks
Published 2023“…The CICIDS2017 dataset includes benign and up-to-date examples of typical attacks, closely matching real-world data of Packet Capture. The four models are tested and assessed using Confusion Metrix against four commonly used criteria: accuracy, precision, recall, and F-measure. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks
Published 2023“…The CICIDS2017 dataset includes benign and up-to-date examples of typical attacks, closely matching real-world data of Packet Capture. The four models are tested and assessed using Confusion Metrix against four commonly used criteria: accuracy, precision, recall, and F-measure. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks
Published 2022“…The CICIDS2017 dataset includes benign and up-to-date examples of typical attacks, closely matching real-world data of Packet Capture. The four models are tested and assessed using Confusion Metrix against four commonly used criteria: accuracy, precision, recall, and F-measure. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks
Published 2023“…The CICIDS2017 dataset includes benign and up-to-date examples of typical attacks, closely matching real-world data of Packet Capture. The four models are tested and assessed using Confusion Metrix against four commonly used criteria: accuracy, precision, recall, and F-measure. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks
Published 2023“…The CICIDS2017 dataset includes benign and up-to-date examples of typical attacks, closely matching real-world data of Packet Capture. The four models are tested and assessed using Confusion Metrix against four commonly used criteria: accuracy, precision, recall, and F-measure. …”
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Article -
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks
Published 2023“…The CICIDS2017 dataset includes benign and up-to-date examples of typical attacks, closely matching real-world data of Packet Capture. The four models are tested and assessed using Confusion Metrix against four commonly used criteria: accuracy, precision, recall, and F-measure. …”
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…To improve the UHDS16 algorithm, 8 × 8 block-matching technique has been tested. …”
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Book Chapter -
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A Study On The Application Of Gravitational Search Algorithm In Optimizing Stereo Matching Algorithm’s Parameters For Star Fruit Inspection System
Published 2018“…This paper reports the result obtained by implementing Gravitational Search Algorithm for tuning Stereo Matching Algorithm’s parameters for the application star fruit inspection system. …”
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GPU-based odd and even hybrid string matching algorithm
Published 2016“…Experimental results indicate that the performance of the hybrid string matching algorithms has been improved, and the speedup, which has been obtained, is considerable enough to suggest the GPU as the suitable platform for these hybrid string-matching algorithms.…”
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Conference or Workshop Item -
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Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…In this project, we will define and discuss the application of evolutionary algorithm in assisted history matching. …”
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Final Year Project -
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…In addition, it is expected that it can be applied in real-time application. In this study, Simulated Kalman Filter (SKF) is applied to image template matching application as the optimization algorithm. …”
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Thesis -
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A Novel Map-matching Algorithm to Improve Vehicle Tracking System Accuracy
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