Search Results - (( code classification problems algorithm ) OR ( wave classification technique algorithm ))
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Classification Analysis Of High Frequency Stress Wave For Autonomous Detection Of Defect In Steel Tubes
Published 2014“…Interpretation of propagated high frequency stress wave signals in steel tubes is noteworthy for defect identification.This paper demonstrated a successful new approach for autonomous defect detection in steel tubes using classification analysis of high frequency stress waves.Classification analysis using Principal Component Analysis (PCA) algorithm involved feature extraction to reduce the dimensionality of the complex stress waves propagation path.Two defective tubes containing a slot defect of different orientation and a reference tube are inspected using Vibration Impact Acoustic Emission (VIAE) technique.The tubes are externally excited using impact hammer.The variation of stress wave transmission path are captured by high frequency Acoustic Emission sensor.The propagated stress waves in the steel tubes are classified using PCA algorithm.Classification results are graphically illustrated using a dendrogram that demonstrated the arrangement of the natural clusters of the stress wave signals.The inspection of steel tubes showed good recognition of defect in circumferential and longitudinal orientation.This approach successfully classified stress wave signals from VIAE testing and provide fast and accurate defect identification of defective steel tubes from non-defective tubes. …”
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A study of frequency radiation of human torso for gender classification
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Working Paper -
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Classification of hand gestures from EMG signals / Diaa Albitar
Published 2022“…This study is to develop classification model to classify six hand gestures using Artificial Intelligent algorithm. …”
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Thesis -
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Human body radiation wave analysis and classification for gender and body segments recognition / Siti Zura A. Jalil @ Zainuddin
Published 2015“…This thesis presents a novel analysis and classification of human radiation wave for gender and body segments recognition. …”
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Book Section -
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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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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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Delineating mangrove forest zone using spectral reflectance
Published 2020“…The use of SID and SAM may provide the most promising classification algorithm for improving mangrove species mapping. …”
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Thesis -
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Human body radiation wave analysis and classification for gender and body segments recognition / Siti Zura A. Jalil @ Zainuddin
Published 2014“…This thesis presents a novel analysis and classification of human radiation wave for gender and body segments recognition. …”
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Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition
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Conference or Workshop Item -
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A multilayered convolutional sparse coding framework for modeling of pooling operation of convolution neural networks
Published 2019“…The multilayered version of CSC(ML-CSC) is shown to be connected to forward pass of CNNs and dictionary learning and sparse coding algorithms of this model are analyzed for solving classification and inverse problems in image processing. …”
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Proceeding Paper -
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Improving hand written digit recognition using hybrid feature selection algorithm
Published 2022“…Therefore, many researchers have applied and developed various machine learning algorithms that could efficiently tackle the handwritten digit recognition problem. …”
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Final Year Project / Dissertation / Thesis -
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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Internal defect detection and reconstruction framework for laminated glass fibre reinforced polymer composite materials
Published 2013“…Increasing the ultrasound system frequency can result in detection of smaller defects but the depth of penetration of the wave decreases. Therefore, an advanced signal processmg technique is necessary to manage large data sets and to extract suitable features for effective internal defect detection. …”
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Analysis of algorithms variation in multilayer perceptron neural network for agarwood oil qualities classification
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Conference or Workshop Item -
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A Naïve-Bayes classifier for damage detection in engineering materials
Published 2007“…The method is based on mean and maximum values of the amplitudes of waves after dividing them into folds then grouping them by a clustering algorithm (e.g. k-means algorithm). …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Beside that, classic bag of visual words algorithm (BoVW) is based on kmeans clustering and every SIFT feature belongs to one cluster and it leads to decreasing classification results. …”
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Adaptive multi-parent crossover GA for feature optimization in epileptic seizure identification
Published 2019“…EEG signal analysis involves multi-frequency non-stationary brain waves from multiple channels. Segmenting these signals, extracting features to obtain the important properties of the signal and classification are key aspects of detecting epileptic seizures. …”
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