Search Results - (( automatic classification using algorithm ) OR ( using solution learning algorithm ))
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…Furthermore, the efficacy of different models based on heuristic hyperparameter tuning is evaluated in which the different kernel function for Support Vector Machine, various distance metrics of k-Nearest Neighbors. 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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Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan
Published 2013“…Sentiment Analysis for Malay Newspaper (SAMNews) is constructed using the negative selection algorithm which is able to classify the sentiment in newspaper’s sentences into the polarity (positive, negative or neutral) automatically repose on detectors word. …”
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Multi-class classification automated machine learning for predicting earthquakes using global geomagnetic field data
Published 2025“…It is concluded that the neural network multi-class classification model is capable of providing solutions to the challenges faced when using geomagnetic data for EQ prediction.…”
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Underwater Image Recognition using Machine Learning
Published 2024“…A Convolutional Neural Network (CNN) is a type of a deep learned an algorithm that has been created for image processing when using convolutional layers to automatically and in a hierarchical way learn features from the input images. …”
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Stage of maturity banana fruit classification using image processing / Nadia Kasim ... [et al.]
Published 2019“…This study attempted to propose a system that uses image processing to detect the maturity stage of banana based on its color and size using Support Vector Machine (SVM) learning algorithm. …”
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Towards a better feature subset selection approach
Published 2010“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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Automatic microsleep detection based on KNN classifier utilizing selected and effective EEG channels
Published 2024“…The selection of an optimum channel and the use of a competent classification algorithm are crucial for effective microsleep detection. …”
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Enhanced extreme learning machine for general regression and classification tasks
Published 2020“…To address this issue, a fast adaptive shrinkage/thresholding algorithm ELM (FASTA-ELM) which uses an extension of forward-backward splitting (FBS) to compute the smallest norm of the output weights in ELM is presented. …”
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Orientation and scale based weights initialization scheme for deep convolutional neural networks
Published 2020“…The filter weights are then automatically learned by the neural network throughout the back- propagation training algorithm. …”
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An enhanced gated recurrent unit with auto-encoder for solving text classification problems
Published 2020“…Gated Recurrent Unit (GRU) is a type of Recurrent Neural Networks (RNNs), and a deep learning algorithm that contains update gate and reset gate. …”
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Automatic classification of medical x-ray images
Published 2013“…These features have been exploited in different algorithms for automatic classification of medical X-ray images. …”
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Decision-Level Fusion Scheme For Nasopharyngeal Carcinoma Identification Using Machine Learning Techniques
Published 2020“…However, the diagnosis accuracy results of such methods are still insignificant and need improvement in order to manifest robust solution. 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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Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition
Published 2021“…FUZZYDBD method, an automatic fuzzy database definition method, would be used to design the fuzzy database for fuzzification of data in the FID3 algorithm. …”
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The use of SOM for fingerprint classification
Published 2023“…The use of efficient classification methods is necessary for automatic fingerprint recognition systems. …”
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Automatic topic-based web page classification using deep learning
Published 2023“…The review process looked at the dataset, features, algorithm, pre-processing used in classification of web pages, document representation technique and performance of the web page classification model. …”
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Automatic Topic-Based Web Page Classification Using Deep Learning
Published 2023“…The review process looked at the dataset, features, algorithm, pre-processing used in classification of web pages, document representation technique and performance of the web page classification model. …”
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Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…This project can be improved by making a comparative study on Artificial Immune System and other techniques or algorithms used to solve dengue classification problems.…”
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