Browsing by Subject "classification"
Now showing items 1-20 of 23
-
A Fitted Fuzzy-rough Method for Missing Data Imputation
( Institute of Electrical and Electronics Engineers Inc. , 2019 , Conference Paper)Missing data imputation is a fundamental task for reducing uncertainty and vagueness in medical dataset. Fuzzyrough set has taken very important role to accurate representation original information. This paper proposes ... -
An Improvement of Support Vector Machine Imputation Algorithm Based on Multiple Iteration and Grid Search Strategies
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)Data missing is a vitally important issue that influences the classification results in medical field. This paper proposes an improved support vector machine (SVM) imputation algorithm by using strategies of pre-imputation, ... -
An intelligent nonintrusive load monitoring scheme based on 2D phase encoding of power signals
( John Wiley and Sons Ltd , 2021 , Article)Nonintrusive load monitoring (NILM) is the de facto technique for extracting device-level power consumption fingerprints at (almost) no cost from only aggregated mains readings. Specifically, there is no need to install ... -
Application of Machine Learning Classification Algorithms for Two-Phase Gas-Liquid Flow Regime Identification
( Society of Petroleum Engineers , 2021 , Conference Paper)This research aims to identify the best machine learning (ML) classification techniques for classifying the flow regimes in vertical gas-liquid two-phase flow. Two-phase flow regime identification is crucial for many ... -
Application of Unsupervised Machine Learning Classification for the Analysis of Driver Behavior in Work Zones in the State of Qatar
( Elsevier , 2022 , Article)Work zone areas are commonly known as crash-prone areas. Thus, they usually receive high priority by road operators as drivers and workers have higher chances of being involved in road crashes. The paper aims to investigate ... -
Automatic and Reliable Leaf Disease Detection Using Deep Learning Techniques
( MDPI , 2021 , Article)Plants are a major source of food for the world population. Plant diseases contribute to production loss, which can be tackled with continuous monitoring. Manual plant disease monitoring is both laborious and error-prone. ... -
Brain Tumor Segmentation and Classification from Sensor-Based Portable Microwave Brain Imaging System Using Lightweight Deep Learning Models
( MDPI , 2023 , Article)Automated brain tumor segmentation from reconstructed microwave (RMW) brain images and image classification is essential for the investigation and monitoring of the progression of brain disease. The manual detection, ... -
Classification of fetal movement accelerometry through time-frequency features
( IEEE , 2014 , Conference Paper)This paper presents a time-frequency approach for fetal movement monitoring which is based on classification of accelerometry signals collected from pregnant women's abdomen. Features extracted from time-frequency distribution ... -
Convolutional Sparse Support Estimator-Based COVID-19 Recognition from X-Ray Images
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)Coronavirus disease (COVID-19) has been the main agenda of the whole world ever since it came into sight. X-ray imaging is a common and easily accessible tool that has great potential for COVID-19 diagnosis and prognosis. ... -
Deep learning based classification of unsegmented phonocardiogram spectrograms leveraging transfer learning
( IOP Publishing Ltd , 2021 , Article)Objective. Cardiovascular diseases (CVDs) are a main cause of deaths all over the world. This research focuses on computer-aided analysis of phonocardiogram (PCG) signals based on deep learning that can enable improved and ... -
Haralick feature extraction from time-frequency images for epileptic seizure detection and classification of EEG data
( IEEE , 2014 , Conference Paper)This paper presents novel time-frequency (t-f) features based on t-f image descriptors for the automatic detection and classification of epileptic seizure activities in EEG data. Most previous methods were based only on ... -
Heterogeneous Multilayer Generalized Operational Perceptron
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)The traditional multilayer perceptron (MLP) using a McCulloch-Pitts neuron model is inherently limited to a set of neuronal activities, i.e., linear weighted sum followed by nonlinear thresholding step. Previously, generalized ... -
Inequality Indexes as Sparsity Measures Applied to Ventricular Ectopic Beats Detection and its Efficient Hardware Implementation
( Institute of Electrical and Electronics Engineers Inc. , 2017 , Article)Meeting application requirements under a tight power budget is of a primary importance to enable connected health internet of things applications. This paper considers using sparse representation and well-defined inequality ... -
Intelligent Fuzzy Classifier for pre-seizure detection from real epileptic data
( Institute of Electrical and Electronics Engineers Inc. , 2014 , Conference Paper)In this paper, a classification method is presented using an Fuzzy Inference Engine to detect the incidences of pre-seizures in real/raw Epilepsy data. The system distinguishes between 'Normal', 'Pre-Seizure' and 'Seizure' ... -
Isolation and Physicochemical Characterization of Laccase from Ganoderma lucidum-CDBT1 Isolated from Its Native Habitat in Nepal
( Hindawi Limited , 2016 , Article)At present, few organisms are known to and capable of naturally producing laccases and white rot fungi are one such group. In the present study, three fungal species, namely, Ganoderma lucidum-CDBT1, Ganoderma japonicum, ... -
Oblique and rotation double random forest
( Elsevier Ltd , 2022 , Article)Random Forest is an ensemble of decision trees based on the bagging and random subspace concepts. As suggested by Breiman, the strength of unstable learners and the diversity among them are the ensemble models’ core strength. ... -
Patient-Specific Seizure Detection Using Nonlinear Dynamics and Nullclines
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)Nonlinear dynamics has recently been extensively used to study epilepsy due to the complex nature of the neuronal systems. This study presents a novel method that characterizes the dynamic behavior of pediatric seizure ... -
Text summarization based on conceptual data classification
( IGI Global , 2008 , Book chapter)In this paper, we present an original approach for text summarization using conceptual data classification. We show how a given text can be summarized without losing meaningful knowledge and without using any semantic or ... -
Text Summarization Based on Conceptual Data Classification
( IGI Global , 2006 , Article)In this article, we present an original approach for text summarization using conceptual data classification. We show how a given text can be summarized without losing meaningful knowledge and without using any semantic ... -
Texture analysis for colorectal tumour biopsies using multispectral imagery
( Institute of Electrical and Electronics Engineers Inc. , 2015 , Conference Paper)Colorectal cancer is one of the most common cancers in the world. As part of its diagnosis, a histological analysis is often run on biopsy samples. Multispecral imagery taken from cancer tissues can be useful to capture ...