Search Results - (( automatic identification using algorithm ) OR ( learning classification using algorithm ))
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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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Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network
Published 2016“…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification
Published 2020“…This study is based on sparse representation-based classification (SRC) theory and the proposed dictionary learning using electroencephalogram (EEG) signals. …”
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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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Speaker identification through feature fusion based deep learning / Rashid Jahangir
Published 2021“…In addition, DNN obtained better classification results compared with the other five machine learning algorithms that were recently utilised in speaker recognition. …”
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A Genetic-CBR Approach for Cross-Document Relationship Identification
Published 2012“…In this work, we aim to automatically identify some of the CST relations using supervised learning method. We propose Genetic-CBR approach which incorporates genetic algorithm (GA) to improve the case base reasoning (CBR) classification. …”
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Fuzzy-based classifier design for determining the eye movement data as an input reference in wheelchair motion control
Published 2015“…Since membership functions (MFs) are generated automatically, the proposed fuzzy learning algorithm can be viewed as a knowledge acquisition tool for classification problems. …”
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Classification Modeling for Malaysian Blooming Flower Images Using Neural Networks
Published 2013“…The appearance of the image itself such as variation of lights due to different lighting condition, shadow effect on the object’s surface, size, shape, rotation and position, background clutter, states of blooming or budding may affect the utilized classification techniques. This study aims to develop a classification model for Malaysian blooming flowers using neural network with the back propagation algorithms. …”
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Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions
Published 2019“…These sensors are pre-processed and different feature sets such as time domain, frequency domain, wavelet transform are extracted and transform using machine learning algorithm for human activity classification and monitoring. …”
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Reassembly and clustering bifragmented intertwined jpeg images using genetic algorithm and extreme learning machine
Published 2019“…The RX_myKarve is an extended framework from X_myKarve, which consists of the following key components: (i) an Extreme Learning Machine (ELM) neural network for clusters classification using three existing content-based features extraction (Entropy, Byte Frequency Distribution (BFD) and Rate of Change (RoC)) to improve the identification of JPEG images content and support the reassembling process; (ii) a genetic algorithm with Coherence Euclidean Distance (CED) matric and cost function to reconstruct a JPEG image from a set of deformed and fragmented clusters in the scan area. …”
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Decision-Level Fusion Scheme For Nasopharyngeal Carcinoma Identification Using Machine Learning Techniques
Published 2020“…The study aim is to develop and propose a new automatic classification of NPC tumor using machine learning techniques and feature-based decision-level fusion scheme from endoscopic images. …”
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Application of artificial neural network in discriminating the agarwood oil quality using significant chemical compounds / Mohd Hezri Fazalul Rahiman … [et al.]
Published 2014“…Back-propagation training algorithm and sigmoid transfer function were used to optimise the parameters in the training network. …”
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Case Slicing Technique for Feature Selection
Published 2004“…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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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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Phylogenetic tree classification system using machine learning algorithm
Published 2015“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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Final Year Project Report / IMRAD -
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Hence, this situation is believed in yielding of decreasing the classification accuracy. In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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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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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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