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298 articles for “multi-class classification”
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Automatic Detection and Classification of Brain Tumor in Magnetic Resonance Images
Abstract: Brain tumor is one of the serious diseases that have caused death to many people in recent years. The complex structure of the brain and its main function associated with the central nervous system and its critical role in controlling most of the functions of the body make detection of tumor a challenging task. Many techniques have been presented in the medical field in order to detect brain tumor from …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 5, Issue 2, 2018 · pp. 34–40 Read article
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Crop Recommendation System Using AI
Abstract: For agriculturists, the online application is useful. In recent few years, experts have become increasingly focused on solid land readiness and its strategy for a variety of reasons. The developing income for agribusiness land and soil thriving evaluation, as well as the strength of the soil, areimportant goals for improving the mark of combination of the examination area. Assessment of the health of the soil and the land, with its …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 13, Issue 1, 2023 · pp. 1–8 Read article
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Convolutional Neural Network and its Architectures
Abstract: Convolutional neural network (CNN) is a type of artificial neural network (ANN) with multiple layers. From the past decades, it has been considered as a powerful classification technique as it can handle a huge amount of imagery data. It can be applied in the field of image recognition. The name CNN has been derived from the mathematical linear operation known as convolution which is performed between two matrices. CNN has …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 2, 2021 · pp. 6–14 Read article
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Object Recognition by Multi-Scale Color Local Binary Pattern
Abstract: This paper presents a multi-scale color local binary pattern based method for object recognition. Several advanced methods have been proposed for object recognition using deep neural networks. Although these methods offer high accuracy with many number of object classes, the high complexity of these methods requires large number of training examples and computational resources. This paper attempts to solve the object recognition problem for limited number of well known object …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 1, 2018 · pp. 57s–61s Read article
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Evolving Perspectives: Innovations in Object Detection and Identification
Abstract: One of the most important developments in computer vision has been the creation of object detection and identification systems, which have allowed robots to perceive and understand visual data similarly to humans. These systems locate each object by drawing a bounding box around it, in addition to detecting and classifying every object in an image or video. This study suggests a novel method for item identification and detection that makes …
Published in Trends in Opto-electro & Optical Communication · Vol. 13, Issue 3, 2023 · pp. 23–27 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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Advances in Lung Cancer Detection and Diagnosis: An Integrative Approach Using Computational Chemistry, Statistics, Bioinformatics, Artificial Intelligence, and Machine Learning
Abstract: Lung cancer is still one of the most common and lethal cancers globally, accounting for more than a million deaths each year. Prompt detection is important, and imaging techniques like chest X-rays, MRIs, PETs, CTs, and molecular imaging have become important tools. But still, even though all these techniques do not provide an accurate classification of the lesion, they have led to the development of computer-based high-resolution image analysis. Computer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Hyperspectral Image Compression and Classification: A Survey
Abstract: The applications of hyperspectral images (HSI) are many, which include agriculture, food quality, remote sensing, medical diagnostics and safety assessment. Hyperspectral image analysis has been used for detecting contaminants and identifying defects in food. It also utilizes advanced software and hardware tools hence allowing users to diagnose and detect pathologies. In this paper an avant-garde investigation about Hyperspectral image compression and classification techniques which can be used in various applications …
Published in Journal of Remote Sensing & GIS Read article
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Characterization and Quality Assessment of Roof Top Harvested Stormwater from four Storage Media in Otukpa, Ogbadibo Local Government Area of Benue State-Nigeria
Abstract: Roof top harvested storm water (RTHSW) from four storage media; Open concrete media (OCM), closed concrete media (CCM), Native pot media (NPM) and Plastic media (PM) used in Ogbadibo LGA of Benue State Nigeria were examined using Spectrophotometric methods, Water quality index (WQI), and multivariate analysis (PCA) performed on the concentration of the water quality parameters for assessment of pollution levels. The test of significance shows high - low positive …
Published in Journal of Water Pollution & Purification Research · Vol. 10, Issue 2, 2023 · pp. 93–105 Read article
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Assessing Land use Dynamics and Policies in the Waghur Basin Using Geospatial Techniques
Abstract: Changes in land use and land cover (LULC) are key indicators of human–environment interactions, especially in river basins where anthropogenic pressure is increasing. This study evaluated land use change and policy implications in the Waghur Basin, India, through a geospatial analysis of 35 years (1990–2025). Remote sensing and GIS-based supervised classification with the help of machine learning methods were applied to multi-temporal Land satellite images to create LULC maps and …
Published in International Journal of Land · Vol. 3, Issue 1, 2026 · pp. 38–49 Read article
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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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Card Fraud Detection Using Artificial Neural Network and Multilayer Perception Algorithm
Abstract: Fraud has posed a significant challenge for merchants, especially in the online business sector, over the course of many years. This is primarily due to the advancements in technology that have made credit card transactions a common method of payment. Credit card fraud refers to the unauthorized use of a credit card by an individual for personal purposes, without the owner's consent and with no intention of paying for the …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 1, 2023 · pp. 21–30 Read article
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Machine Learning Approach to Detect and Analyze Attention-Deficit/Hyperactivity Disorder
Abstract: Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder characterized by difficulties with attention, impulse control, behavioral regulation, and daily functioning that persist across childhood and adulthood. Clinical diagnosis is predominantly based on behavioral assessments and expert interpretation, which may result in subjectivity and delayed clinical decisions. To reduce reliance on subjective evaluation, this study introduces an automated ADHD identification framework that integrates resting-state functional Magnetic Resonance Imaging (rs-fMRI) with advanced machine …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 22–26 Read article
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Study of High-rise Building with Varying Imposed Loads Condition for Lateral Load Excitation
Abstract: The demand for land has risen, causing scarcity and leading to a significant increase in the construction of tall residential and commercial buildings. With limited land and a growing population, expanding horizontally is not feasible, making multistory buildings the solution. Urbanization has led to the construction of numerous high-rise structures, emphasizing the need for a thorough understanding and analysis of these structures. The present study aims to determine the critical …
Published in Journal of Structural Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 92–106 Read article
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Hand-Tracking-Based Mouse Control for Touchless Human-Computer Interaction: Feasibility and Future Enhancement
Abstract: This paper presents a novel approach to human-computer interaction through a hand-tracking-based mouse control system using computer vision. The system utilizes OpenCV, MediaPipe, and the Cvzone Hand Tracking Module to identify and monitor hand movements in real-time. By utilizing hand landmarks, the system maps finger positions to cursor movement and enables essential functions such as clicking, scrolling, and double-clicking. The primary motivation for developing this system is to create a …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 · pp. 18–25 Read article
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Trend analysis of Normalized Difference Vegetation Index using Landsat Satellite data: Study from in and Gondar town, North West Ethiopia
Abstract: Abstract This current research study presents the change detection method for the study of Satellite image supported on Normalized Difference Vegetation Index (NDVI). NDVI utilizes the Multi-Spectral remote sensing data method to determine Vegetation Index, land cover classification, vegetation, water bodies, bush land, agricultural area, thick forest and thin forest with few bands grouping of the remote sensed data. Land resources are easily understood by calculating their Normalized Difference Vegetation …
Published in Journal of Control & Instrumentation · Vol. 10, Issue 3, 2019 · pp. 25–33 Read article
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A Study of Diabetic Retinopathy using Convolutional Neural Networks
Abstract: This paper focuses on study of rapid detection of retinopathy, since prompt therapy can help decrease as well as possibly eliminate loss of eyesight. Furthermore, automatically locating portions of the optic picture which may include lesions could aid professionals in their identification function. Retinopathy is a frequent diabetic condition that comprises changes in the retinal blood capillaries. Such changes may lead capillaries to rupture as well as release fluid, causing …
Published in Journal of Instrumentation Technology & Innovations · Vol. 12, Issue 2, 2022 · pp. 1–6 Read article
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Land Use/Land Cover Change Detection Analysis Using Supervised Classification, Remote Sensing and GIS In Mandavi River Basin, YSR Kadapa District, Andhra Pradesh, India
Abstract: Assessment, development, and management of watershed strategy require exact calculations reports of present and past land use/cover data and its change determine the ecological and hydrological process taking place in a watershed. In this study, we have to adopt supervised classification with maximum likelihood algorithm in ERDAS imagine to notice land use/cover changes (LU/LCC) analyzed in Mandavi river basin, Kadapa district, Andhra Pradesh, India using multispectral satellite data gained from …
Published in Journal of Remote Sensing & GIS · Vol. 9, Issue 3, 2018 · pp. 46–54 Read article
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OQPMSAV: Opportunistic Quality of Services Provisioning for Multimedia Services using Artificial Neural Network
Abstract: Vehicular ad hoc network is used to provide services related to traffic safety and user requirements. In VANET, applications are designed for users from various domains automobile company, road safety authority, advertisement industries, personal entertainment. Applications developer requires efficient utilization of available networking resources. VANET is witnessed of continuous support form researchers, developer, government authorities and vehicles manufactures. In VANET, vehicles are designed to move at high speed which causes …
Published in Journal of Communication Engineering & Systems · Vol. 8, Issue 1, 2018 · pp. 29–42 Read article
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SYNERGISTIC FUSION OF HYPERSPECTRAL AND HIGH RESOLUTION IMAGE FOR IMPROVING PERFORMANCE AND RELIABILITY OF AUTOMATICALLY EXTRACTED URBAN FEATURES
Abstract: Image fusion is a generic word referring to several techniques of digital image processing which are used to integrate data from different spatial and spectral resolutions in order to obtain higher-quality synthetic images. This paper emphasizes the assessment and systematic analysis of image fusion techniques by measuring the quantity of enhanced information in fused images. EO1- Hyperion and IKONOS (MSS+PAN) have been fused using Principal component analysis, Gram-Schmidt Transformation (GST) …
Published in Journal of Remote Sensing & GIS · Vol. 1, Issue 1, 2010 · pp. 1–11 Read article