Search Results - (( using identification method algorithm ) OR ( learning classification using 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“…The combination of gist, MTH and SIFT features increased the performance of image identification and showed 49% accuracy. Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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2
Automated system for concrete damage classification identification using various classification techniques in machine learning / Nur Haziqah Mat ... [et al.]
Published 2021“…This invention can recognize a certain damage while the classification of defects is classified according to the features extracted from the images by using GLCM algorithm. …”
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3
Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga
Published 2022“…First, to investigate the methods used to address limitations associated with microbiome-based datasets in colorectal cancer identification using deep neural network algorithms. …”
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Gender identification using support vector machines
Published 2023“…Support vector machine (SVM) is a popular technique for classification. It is one of the recent methods for statistical learning and also addresses classification and regression problems. …”
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5
Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…Optimization algorithms are widely used for the identification of intrusion. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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Next generation insect taxonomic classification by comparing different deep learning algorithms
Published 2022“…Conventional methods used to study insect taxonomy are often tedious, time-consuming, labor intensive, and expensive, and recently, computer vision with deep learning algorithms has offered an alternative way to identify and classify insect images into their taxonomic levels. …”
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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. In this paper, the efficiency of deep learning algorithms in classifying the growth stage of chili plants is studied. …”
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Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh
Published 2020“…This study proposed an integrated system for EEG signals pre-processing by using machine learning algorithms in the identification of artifactual components during the process of Wavelet-ICA. …”
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10
Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy
Published 2020“…Therefore, we aimed to classify six classes of freshly excised tissues from a set of electrical impedance measurement variables using five ensemble-based machine learning (ML) algorithms, namely, the random forest (RF), extremely randomized trees (ERT), decision tree (DT), gradient boosting tree (GBT) and AdaBoost (Adaptive Boosting) (ADB) algorithms, which can be subcategorized as bagging and boosting methods. …”
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11
A COLLABORATIVE FRAMEWORK FOR ANDROID MALWARE IDENTIFICATION USING DYNAMIC ANALYSIS
Published 2019“…The machine learning algorithm is used to train and test datasets with the percentage of 70% which is 140 samples from malware and benign applications and 30% of total datasets which is 60 samples from malware and benign applications respectively. …”
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Review of Wheat Disease Classification and Severity Detection Models
Published 2023“…To combat these diseases, researchers have been studying the use of advanced techniques such as deep plant disease learning and image processing methods for identification. …”
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Identification model for hearing loss symptoms using machine learning techniques
Published 2014“…The model is implemented using both unsupervised and supervised machine learning techniques in the form of Frequent Pattern Growth (FP-Growth) algorithm as feature transformation method and multivariate Bernoulli naïve Bayes classification model as the classifier. …”
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14
Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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Odour based human identification and classification using neural networks
Published 2019“…The unsurpassed framework for algorithm learning to be used for human identification can be back propagation learning algorithm named the Levenberg-Marquardt. …”
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Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida
Published 2019“…Combinations of feature selection and classification algorithms were used for mortality prediction post ACS. …”
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Classification of Learner Retention using Machine Learning Approaches
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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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Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari
Published 2018“…For the ANN, Multilayer feed-forward networks are trained using Back Propagation (BP) learning algorithm and for the KNN, is used the most common distance which is Euclidean. …”
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