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235 articles for “classification”
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Advances in Gender Classification from Facial Images Using CNNs: A Comprehensive Review
Abstract: Predicting age and gender from facial images is important for various uses, like social interactions, security, and customizing user experiences. Despite progress in facial recognition technology, getting accurate and reliable predictions is still a challenge. This paper reviews recent advancements in Convolutional Neural Networks (CNNs) for age and gender classification, comparing their effectiveness to traditional methods. CNNs excel in extracting features from images and have shown notable improvements in accuracy …
Published in International Journal of Digital Communication and Analog Signals · Vol. 10, Issue 2, 2024 · pp. 1–5 Read article
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A Comparative Study Of RCNN, YOLO V3-Tiny and YOLO V5 Object Classification Architectures for Accurate Object Classification in Military Domain
Abstract: Late advances in object distinguishing proof computations consolidate speedy and faster RCNN whichmade the ID times also low with high accuracy. In this paper, we demonstrate the reliability of asuggested computation that employs RPN (Region Suggestion Associations) and Fast RCNN (RegionbasedConvolutional Neural Networks) for the distinguishing proof. The RPN gives region suggestionsfrom that we give the ROI (Regions of Interest) as commitment to the RCNN association, it will ingeneral be …
Published in International Journal of Broadband Cellular Communication · Vol. 7, Issue 1, 2021 · pp. 19–37 Read article
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Classification of power quality disturbances using advanced deep learning algorithms for Accurate and efficient electrical signal analysis
Abstract: Power systems today have to deal with more and more power quality issues (PQDs) like voltage drops, rises, harmonics, and transients because more people are using renewable energy sources and electronic devices. These problems can hurt equipment, stop services, and lower the overall reliability of power. In real-time settings, traditional detection methods often don't work as quickly or accurately as they should. This paper looks at how deep learning models, …
Published in International Journal of Power Electronics Controllers and Converters · Vol. 12, Issue 2, 2026 Read article
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A Smart Recommendation System for Carrier Shipper Matching Using Multilabel Classification – A Survey
Abstract: Efficient matching between carriers and shippers is crucial in the logistics industry to optimize resource utilization and minimize costs. This paper puts forth a smart recommendation framework dependent on multilabel classification techniques to improve the carrier-shipper matching process. The method makes use of machine learning techniques to predict multiple relevant carrier options for a given shipment request. We present a comprehensive literature review on related works in carrier-shipper matching and …
Published in International Journal of Broadband Cellular Communication · Vol. 10, Issue 1, 2024 · pp. 1–7 Read article
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Support Vector Machine-based Flower Image Classification for Commercial Applications
Abstract: Flowers are crucial raw materials in many industries, including pharmaceuticals and cosmetics. Classifying flowers manually is time-consuming, inconsistent, and requires professional judgment from a botanist. Computer-aided flower classification is a promising approach to this problem. Image classification often employs support vector machines (SVMs) as widely favored algorithms. This study evaluated the performance of SVMs for flower image classification. The results showed that SVMs can achieve good accuracy on this task, …
Published in International Journal of Software Computing and Testing · Vol. 9, Issue 2, 2023 · pp. 44–53 Read article
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A Review on Design and Analysis Model for Detectionand Classification of Lung Diseases Using Medical Images
Abstract: A key component of the human respiratory system, the lung regulates blood oxygen levels through gasexchange. Diseases linked to the lungs are becoming more common as pollution levels rise. In order topreserve human life, it is crucial to identify lung disorders early. In order to forecast lung disease, clinicalprofessionals analyze medical imaging, such as CT or X-rays. Clinicians identify lung disease by applyingtheir medical expertise and knowledge. Because expert knowledge …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 2, 2025 Read article
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Speech Emotion Recognition using Multi- Kernel CNN for Features extraction and Random Forest Classifier
Abstract: Identifying human emotional states from speech signals is the main goal of Speech Emotion Recognition (SER), which has grown to be a significant area of study in affective computing. However, class imbalance and efficient feature extraction from speech data pose problems for many of the current methods. This study suggests a hybrid framework that combines a Random Forest (RF) classifier with a multi-kernel Convolutional Neural Network (CNN) to address these …
Published in International Journal of Digital Communication and Analog Signals · Vol. 12, Issue 2, 2026 Read article
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Evaluation of Machine Learning and Deep Learning Models for Classification Tasks on Crime Data: A Comparative Study
Abstract: The classification of crime data has grown more and more important for public safety and law enforcement due to the increasing demand for precise and effective predictive models. To classify crime data, this study assesses and contrasts the effectiveness of several machine learning (ML) and deep learning (DL) models, such as decision trees, support vector machines, neural networks, and convolutional neural networks. The study evaluates the models' accuracy, efficiency, and …
Published in International Journal of Digital Communication and Analog Signals · Vol. 11, Issue 1, 2025 · pp. 1–15 Read article
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Comparative Study of Classification Methods Based on Feature Reduced Microarray Gene-Expression Data
Abstract: Abstract Cancer is a very complex and clinical heterogeneous disease. Now a days the research into the diagnosis and treatment of cancer have become an important issue for researchers. Cancer microarray data normally consist of samples having large number of gene expression as features. For better result in cancer classification it is very important to select relevant features. In this paper, five different types of cancer datasets are used such …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 1, Issue 2, 2015 · pp. 1–10 Read article
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Facial Expression Classification using Multi-Scale Histogram of Oriented Gradients
Abstract: An automatic facial expression classification method, based on multiscale Histogram of Oriented Gradients (HOG) features extracted from sub-facial image patches, is proposed in this paper. A number of multiclass Support Vector Machines (SVM) are designed using the multiscale HOG features for classifying six basic facial expressions for frontal face images. The proposed method, with a simple design and few training data, achieves descent classification accuracy at a very low computational …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 6, Issue 1, 2020 · pp. 5–13 Read article
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Classification and Detection of Cabbage Leaf Diseases from Images Using Deep Learning Methods
Abstract: The presented work uses Deep learning methods to detect diseases in cabbage leaves. To avoid a reduction in agricultural product yield, disease diagnosis in plants is crucial. Manual plant disease monitoring is challenging and time-consuming at every stage. Five major types of diseases are considered. Initially, the input images are classified as healthy and diseased. Further, the diseased images are classified into five different varieties. Early and precise biotic stress …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 8, Issue 2, 2022 · pp. 23–32 Read article
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Sound-based Bird Classification Using Perceptual Features and Machine Learning: A Gaussian Mixture Model
Abstract: Classification of birds based on their sound patterns and identification of bird species found in the chirping sounds of birds were experimented with using the feature extraction method. This work is beneficial in ornithology to study birds and their behavior based on their sounds. The proposed methods can automatically classify birds by different sound processing. The audio file of a bird’s sound recording is first cut into smaller samples, and …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 9, Issue 2, 2023 · pp. 46–52 Read article
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Review on GABASS (Genetic Algorithm Based Attributes Subset Selection) Using Naïve Bayes Classifier
Abstract: ABSTRACT In the present work, review on Genetic Algorithm based Attributes Subset Selection using Naïve Bayes Classifier is presented. A dataset can contain a few components. Many clustering strategies are intended for grouping low-dimensional information. In highdimensional space discovering groups of information objects is trying because of the scourge of dimensionality. At the point when the dimensionality expands, information in the immaterial measurements may create much commotion and veil the …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 4, Issue 2, 2018 · pp. 21–27 Read article
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Blood Cell Subtype Classification Using Deep Learning
Abstract: A vital component of human bodies is blood. Despite making up only 1% of the human body, blood cells have a greater impact on disease and infection detection. These blood cell subtype classifications also aid in ensuring that patients receive the quickest-acting medical treatment and recover swiftly. To get the findings, many machine learning techniques are used, including the Feature Extraction methods (K* classifier and Decision table) and the Image …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 9, Issue 1, 2023 · pp. 37–45 Read article
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An Introduction of Nanotechnology: Classification, Uses, and Applications of Nanomaterials
Abstract: Nanomaterials (NMs) have acquired noticeable quality in creative advancements due to their tuneable physical, synthetic, and organic qualities with improved performance over their mass counterparts. The order of the NMs is determined by their size, creation, form, and starting. The ability to predict the unique features of NMs increases the value of each order. Because of the increased growth of NM creation and their current uses, difficulties relating to harmfulness …
Published in International Journal of Composite and Constituent Materials · Vol. 7, Issue 2, 2021 · pp. 31–38 Read article
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Fault Diagnosis of Helical Gear Box Using Variational Mode Decomposition with Naïve Bayes and Bayes Net Classifiers through Vibration Signals
Abstract: Gear is a very important machine component which finds use in most of the machines which requires some sort of power transmission or reduction. Unattended faults in gears can be catastrophic for the machine leading to halts in production and consequent economic loss. The requirement for a gear fault detection and diagnosis system is thus emphasized. Vibration signals are often used in fault diagnosis applications along with Fast Fourier transform …
Published in International Journal of Manufacturing and Materials Processing · Vol. 1, Issue 1, 2014 · pp. 1–16 Read article
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Edge AI-Based Smart Passenger Protection Systemwith Accident Severity Classification andAutonomous SOS Communication
Abstract: This project presents the design and implementation of an Edge AI-Based Smart Passenger Protection System to enhance passenger safety during hazardous situations inside vehicles. The system integrates an MQ-2 gas sensor, an impact sensor, an Edge AI-enabled microcontroller, a two-channel relay module, and a buzzer to provide intelligent and autonomous safety responses in real time. The gas sensor continuously monitors the air quality inside the vehicle cabin, while the Edge …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 12, Issue 2, 2026 Read article
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Artificial neural network based classification of varieties of thin and thick fabric images
Abstract: Abstract: The proposed work focuses on classification of varieties of thin and thick fabric materials from images. The morphological operations such as erosion and dilation are performed. Morphological features namely, avg_moments, average_area, roundness, max_area, average_perimeter, average_eccentricity, circularity and average_equivalent_diameter are extracted. The prediction is carried out using artificial neural network. The classification rates of 84.84% and 90.90% are obtained for thin and thick fabric images. The classification rates for varieties …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 4, Issue 1, 2018 · pp. 31–41 Read article
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Fuzzy and Intuitionistic Fuzzy Operators with Applications in Breast Tumor Classification
Abstract: Breast Cancer accounting for 14% of all cancers in women is the most familiar cancer among women in India. According to GLOBOCON data 2018, 1,62,468 new cases and 87,090 demises were accounted for breast cancer in India. The incidence rate of breast cancer starts rising in the early 30s and reaches a peak at the age of 50–64 years. In general, 1 in 28 women will develop breast cancer at …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 9, Issue 1, 2023 · pp. 35–46 Read article
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ANN Based Power Quality Identification and Classification in Wind Solar Hybrid System
Abstract: With the development of new functionalities solar and wind energy based hybrid system are upcoming energy source with higher efficiency. Solar and wind energy being naturally available in abundance and non-polluting is one of the most promising sources. Due to the development of modern power electronics devices the power quality of wind solar hybrid system gets affected. Hence due to the increasing usage of sensitive electronic equipments in wind solar …
Published in International Journal of Electrical Power System and Technology · Vol. 3, Issue 2, 2017 · pp. 6–11 Read article