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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs
Published 2021“…Finally, the k-nearest neighbors ( kNN) classification technique was used for automatic gender identification of an emotional-based EEG dataset. …”
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Object-Oriented Programming semantics representation utilizing agents
Published 2011“…Novices tend to refer to source codes examples and adapt the source codes to the problem given in their assignments. …”
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Feature extraction using spectral centroid and mel frequency cepstral coefficient for Quranic accent automatic identification
Published 2014“…This paper presents the process of Quranic Accent Automatic Identification. Recent feature extraction technique that is used for Quranic verse rule identification/Tajweed include Mel Frequency Cepstral Coefficients (MFCC) which prone to additive noise and may reduce the classification result. …”
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Scene classification for aerial images based on CNN using sparse coding technique
Published 2017“…Recent developments include several approaches and numerous algorithms address the task. This article proposes a convolutional neural network (CNN) approach that utilizes sparse coding for scene classification applicable for HRRS unmanned aerial vehicle (UAV) and satellite imagery. …”
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Maldroid- attribute selection analysis for malware classification
Published 2019“…Hence, the objective of this paper is to find the most effective and efficient attribute selection and classification algorithm in malware detection. Moreover, in order to get the best combination between attribute selection and classification algorithm, eight attributes selection and seven categories machine learning algorithm are applied in this study. …”
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Scene classification for aerial images based on CNN using sparse coding technique
Published 2023Article -
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A multi-color based features from facial images for automatic ethnicity identification model
Published 2019“…Finally, the proposed ethnicity identification was tested using several classification algorithms. …”
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Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification
Published 2020“…In this research, a fully automated system is presented to automatically detect the various states of the epileptic seizure. …”
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System Identification And Control Of Automatic Car Pedal Pressing System For Low-Speed Driving In A Road Traffic Delay
Published 2022“…Both controllers were then implemented and tested in automatic car pedal pressing system. The controller gains were tuned using metaheuristic algorithm which is Particle Swarm Algorithm (PSO) for optimal values of fuzzy controller parameters. …”
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Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition
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Smart Cards And The Fingerprint : A Proposed Framework For The Automatic Teller Machine (ATM) System
Published 2002“…As a result, the research proposed a framework for user identification and authentication in automatic teller machine (ATM) systems using fingerprints and smart cards as opposed to the PIN and magnetic-stripe cards. …”
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Analysis of minutia extraction techniques in fingerprint recognition.
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Fault identification in pipeline system using normalized hilbert huang transform and automatic selection of intrinsic mode function
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Online fingerprint recognition
Published 2010“…Fingerprints are the most popularly used in biometric identification and recognition systems, because they can be easily used and their features are highly reliable. …”
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The efficacy of deep learning algorithm in classifying chilli plant growth stages
Published 2021“…The demand in this field has created various opportunities, especially for automatic classification using deep learning methods. …”
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