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433 articles for “neural network method”
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Design of a Powerful Brightness Measurement and Exposure Control Method for Real-Time Video Recording
Abstract: The auto exposure control (AEC) device in a video camera selects the right aperture length, advantage putting, and publicity time such that the publicity best suits the scene brightness. although some strategies to AEC had been proposed, maximum of them lack smart mechanisms to quickly estimate the proper exposure whilst users suddenly alternate the scene. The method to Match the brightness of the scene, the Auto Exposure Control (AEC) system …
Published in Journal of Microelectronics and Solid State Devices · Vol. 9, Issue 1, 2022 · pp. 1–5 Read article
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A Machine Learning-based Analysis of Climate Change
Abstract: Climatic variations are a pressing global challenge that demands immediate and comprehensive attention. A wealth of articles has been published on climate change mitigation and adaptation, yet there remains a need for innovative methods to explore the complexities of climatic variations and to devise more efficient and effective strategies for adjustment and alleviation. With technological advancements, machine learning (ML) and deep learning (DL) approaches have derived significant popularity across various …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 1–10 Read article
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Detection of Phishing Website Using URL
Abstract: Phishing attacks are one of the greatest threats to online security, where fraud websites deceive users into giving out sensitive information. Traditional methods of detection, such as blacklists and heuristic-based systems, often fail in identifying newly created or sophisticated phishing websites. This study proposes an intelligent phishing website detection system using Convolutional Neural Networks (CNNs) in analyzing URLs and associated features. Using labeled URLs, the system employs such attributes such …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 10–15 Read article
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An Approach of Multi-modal Biometric Iris and Speech based Person Recognition System with Decision Fusion Technique
Abstract: This paper presents a unique approach of multi-modal iris and speech feature based person recognition system. Iris images and speech signals are taken from CASIA iris database and NOIZEUS speech database respectively. Iris features are extracted after applying iris images noise removing and image pre-processing techniques. On the other hand, speech signal noise removing, start-end points detection algorithm, silence parts removal, windowing and feature extraction techniques are applied to extract …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 2, Issue 2, 2015 · pp. 5–10 Read article
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Review of Deep Learning in Medical Imaging
Abstract: In the past few years, computer-aided analysis has fallen quickly behind. Organ categorization and segmentation is a key stage in computer-aided diagnosis. In recent years, there has been a lot of interest in the division of abdominal organs such as the liver, stomach, kidney, pancreas, and bladder from various picture modalities. Radiologists or medical specialists analyze abdominal pictures the majority of the time. Due to subjectivity, intricacy of the picture, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 3, 2022 · pp. 16–24 Read article
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Numerical Simulation of Deep Convolutional Neural Network Based Flower Classification System
Abstract: There are more than 250,000 recognized floral plant forms in 350 families. Further more the order, the plant checks of structures, the gardening industry, live plantations and scientific flower classification instructions depend on fruitful flower classification, including a content-based image recuperation. A wide range of applications also includes flower portrayals. The manual classification is however tedious and tiresome, particularly when the picture foundation is perplexing, with a huge number of …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 3, 2021 · pp. 23–31 Read article
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Enhanced Deep Learning Techniques for Defect Detection in Steel-Fiber-Reinforced Composites: A Comparative Study of KerasTuner, CNN–PSO, and CNN–GWO
Abstract: The identification of microstructural defects in steel-fibre-reinforced composites is useful for the material integrity, mechanical reliability and longevity. Classic material inspection techniques face difficulties in recognizing the complex and visually similar defects because of heterogeneous material morphology, changing imaging conditions, and limits of manual feature extraction. To tackle those problems, this study presents a comparative deep-learning framework that integrates Convolutional Neural Networks (CNNs) with three hyperparameter optimization techniques namely KerasTuner, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 · pp. 377–403 Read article
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Statistical Models for Predicting Genetic Variability and Disease Susceptibility
Abstract: Differences in genetics are key to understanding why some individuals are more prone to certain diseases than others. Recent advancements in genomic research, combined with statistical modeling techniques, have made significant strides in predicting disease risk based on genetic factors. This review explores the application of statistical models for predicting genetic variability and their role in disease susceptibility. We discuss traditional methods like linear regression and genome-wide association studies (GWAS), …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 30–34 Read article
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Tensor-Flow Based Approach to Identify Author of the Text
Abstract: Now-a-days a lot of content is available on internet, and people upload lot of information in form of opinion, review, description, recipe etc. online. In such scenario to trace the authenticity of the data, it is necessary to develop an author identification system. It has become a difficult problem in the scope of unnamed information has increased with fast growing Internet life. It is a process to identify author of …
Published in Current Trends in Information Technology · Vol. 8, Issue 3, 2018 · pp. 23–29 Read article
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A Comparative Machine Learning Framework for Early Prediction of Liver Cancer Using Clinical Attributes
Abstract: One of the main causes of cancer-related death globally is liver cancer, and improving patient outcomes depends heavily on early detection. However, low contrast, noise, organ similarity, and tumor shape and size variability make it difficult to accurately identify and segment liver tumors from medical imaging. Automated liver cancer diagnosis, segmentation, and prognosis have been greatly improved by recent developments in artificial intelligence (AI), especially deep learning. This work presents …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 · pp. 39–47 Read article
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AbhiGyam: A Machine Learning Model-driven Research Platform for Assessing Accessibility Infrastructure in Indian Cities
Abstract: This work presents AbhiGyam, a machine learning-driven research platform designed to streamline and automate the assessment of accessibility infrastructure in Indian cities. AbhiGyam leverages the Google Maps API to transmit street view images to the backend, where computer vision techniques are implemented using OpenAI's CLIP (Contrastive Language-Image Pre-training) model to identify objects such as ramps, sidewalks, crosswalks, and parking spaces. The accuracy of the model is validated using labeled data …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 84–91 Read article
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Mode Choice Analysis: Fundamental and Models
Abstract: AbstractTravel behavior plays an important role in transportation planning. Mode choice has direct impact on the policy making decision. It is behavioral and complex in nature. The objective of this study is to carryout detailed review on various modeling methods of mode choice analysis. The factors that affect the traveler’s mode choice decision have been discussed. The methods of data collection have been briefly discussed. Further the paper highlights on …
Published in Trends in Transport Engineering and Applications · Vol. 5, Issue 1, 2018 · pp. 7–13 Read article
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Analysis of Various Diabetes Prediction Techniques Based on Machine Learning
Abstract: AbstractData mining is a method of mine from the underdone data for maintains useful information. In organize to obtain fundamental knowledge it is important to remove bulky quantity of data. This method is consist of many important components like data cleaning, data selection, data integrity, pattern evaluation with data mining engine and database with graphical user interface. Diabetes is a chronic disease that is also known as Non‐Insulin Dependent Diabetes …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 1, 2021 · pp. 17–22 Read article
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Detection of Cardiovascular Disease using AI and ML: A Review
Abstract: In the 21st century according to statistics, the risk of cardiovascular disease has become more common and the death rate caused by it is increasing way more. Around 17.9 million lives are taken by CVDs each year. There are various reasons causing it but most importantly it is caused by not identifying it, hence it becomes a very important task for the human race to identify the CVDs and deal …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 11–21 Read article
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SATELLITE IMAGE CLASSIFICATION USING MACHINE LEARNING
Abstract: Satellite imagery is used in for various applications such as disaster management, defence, surveys, and environmental understanding. Earlier, manual processing was applied to do analysis. These methods are not accurate to detect the target and classify the object. Hence, in this work machine learning is explored. Now a days deep learning has gain prominence to automate target detection and classification. Convolutional Neural Networks (CNN) are playing vital role in deep …
Published in Journal of Remote Sensing & GIS · Vol. 12, Issue 2, 2021 · pp. 10–18 Read article
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A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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Classification of Skin Disease Images Using EfficientNetTransfer Learning Technique
Abstract: Melanomous Skin lesions are among the deadliest kinds of cancer. Despite being a very uncommon skin condition, melanoma is responsible for 75% of cancer-related deaths. Dermatologists perform dermoscopy more commonly than any other procedure. Since it aggravates the skin condition, a dermatologist will be the first to identify it during an inspection. Because this strategy depends on the user's visual perception and experience, it can only be used by highly …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 · pp. 7–12 Read article
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A study in Leveraging Deep Learning and IoT Arrays for Dynamic, Hyper-Local Atmospheric Intelligence
Abstract: The critical demand for high-resolution, actionable atmospheric data is challenged by the high cost and sparse coverage of traditional regulatory monitoring stations. This paper explores the synergistic paradigm shift enabled by integrating low-cost, dense Internet of Things (IoT) sensor arrays with advanced Artificial Intelligence (AI) methodologies, specifically Deep Learning (DL) models. We address the primary limitations of low-cost sensors—inherent bias, sensitivity to environmental drift (temperature/humidity), and calibration inconsistency—by utilizing AI …
Published in International Journal of Atmosphere · Vol. 2, Issue 2, 2025 · pp. 50–62 Read article
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Enhancing Energy Storage and Optimization of Distributed Energy Resources Using a Hybrid SWOA-MSNN Approach
Abstract: The fast growth of Distributed Energy Resources (DERs) like solar photovoltaics, wind power, and energy storage devices requires enhanced optimization methods to manage energy efficiently and stabilize operations in contemporary smart grids. A significant challenge is the dynamic optimization of the energy storage systems (ESS) and the distribution of the energy among DERs in conditions of uncertainty of loads and generation. The conventional control and optimization methods generally find it …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article
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Video Resolution Enhancement
Abstract: In this period of advanced correspondence, video has become a significant aspect of our everyday life. Additionally, video enhancement being a functioning exploration subject in PC vision has gotten more consideration in these ongoing years. Video enhancement manages the accompanying issue: Given an inferior quality info video, how might we make yield video more understood and better". There are essentially two strategies for video enhancement: 1-Spatial - based space video …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 10, Issue 1, 2021 · pp. 50–56 Read article