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398 articles for “Neural Network Techniques”
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A Study of Hand Gesture Identification with Convolution Neural Network
Abstract: Human-Computer Interaction is the study of how the people interact with machine. Hand gesture technology is active research in computer vision and machine learning. Hand gesture recognition is used enormously in the recent years for Human Computer Interaction (HCI). In this research work, we study about hand gesture identification with machine learning technique. Basically implementation of hand gesture identification has three phases: Preprocessing, Feature extraction, and Classification. This study includes …
Published in Recent Trends in Programming languages · Vol. 8, Issue 1, 2021 · pp. 30–34 Read article
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Role of Machine Vision in Autonomous Vehicles: A Review
Abstract: The integration of machine vision in autonomous vehicles (AVs) is a critical advancement in the field of intelligent transportation systems. Machine vision systems enable AVs to perceive their environment, understand road conditions, detect obstacles, and make real-time decisions necessary for safe navigation. These systems rely heavily on image processing techniques, which have evolved significantly over the past decade, leading to improved performance in complex driving scenarios. These developments are largely …
Published in Trends in Machine design · Vol. 12, Issue 1, 2025 · pp. 38–43 Read article
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Artificial Intelligence for Real-time Water Management
Abstract: Effective water management is vital for sustainable development, requiring the strategic allocation and utilization of water resources to satisfy the diverse demands of agriculture, industry, and households. Traditional methods are increasingly inadequate due to escalating challenges from climate change and population growth, which amplify water scarcity and distribution issues. To overcome these challenges, we need innovative solutions. Artificial intelligence offers significant potential in revolutionizing realtime water management through advanced techniques …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 13–20 Read article
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Secure Data Processing and Transmission Using Machine Learning Techniques
Abstract: The amount of data created by smart devices has drastically increased in recent years as a result of the quick technological improvements in those devices and their use in a variety of applications. As a result, the big data (BD) created by various devices may be too much for typical data analytics tools to handle. However, this exponential expansion of data provides numerous types of attackers with new chances to …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 9, Issue 3, 2022 · pp. 22–30 Read article
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Ventricular Arrhythmia Detection Techniques for ECG Signal: A Survey Approach
Abstract: Electrocardiogram (ECG) represents the electrical activity of the heart and is used to measure the rate and regularity of heartbeats. In this paper we propose a method for an Independent Component Analysis (ICA) based detection and classification of the ventricular arrhythmia. The malignant ventricular arrhythmia database from www.physionet.org/physiobank/database/vfdb has been utilized for evaluating the algorithm over MATLAB interface. This scheme assimilates ICA and probabilistic neural network for classifying critical arrhythmia …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 5, Issue 1, 2015 · pp. 25–30 Read article
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Hybrid HMM/ANN Models for Improving Offline Handwritten Text Recognition
Abstract: AbstractIn this approach, it proposes the use of hybrid Hidden Markov Model (HMM)/Artificial Neural Network (ANN) models for recognizing the unconstrained offline handwritten texts. Handwritten image normalization from a scanned image includes several steps, usually it begin with image cleaning, page skew correction, and line detection. For handwritten text line image several pre-processing steps to reduce variation in writing style are performed like slope and slant removal and character size …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 3, 2016 · pp. 16–23 Read article
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Block Chain Based Supply Chain for Grading Milk Quality Using Machine Learning Techniques
Abstract: Milk is a primary source of nutrition in practically every country on the globe. Milk is widely packaged in a variety of containers such as packages, cans, glass bottles, and polyethylene terephthalate (PET) bottles. Milk, on the other hand, has a limited period for the customer to use it because it has an expiration date. Despite the clearance of the expiration date, it is possible that the milk could have …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 2, 2023 · pp. 80–92 Read article
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Advances in Deep Learning for Medical Image Analysis in the Era of Precision Medicine
Abstract: Medical imaging is fundamental to modern healthcare but analyzing the high-dimensional data requires advanced techniques. Manual image interpretation is time-consuming, subjective and limited in detecting complex patterns and minute details. Recent breakthroughs in Deep Learning offer transformative advances for unlocking clinically relevant information from medical images. This paper provides a comprehensive 6000+ word review of the current state-of-the-art Deep Learning techniques for medical image analysis including detailed coverage of key …
Published in Research and Reviews : Journal of Computational Biology · Vol. 12, Issue 2, 2023 · pp. 10–23 Read article
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Smart Polymer Composites with Multifunctional Capabilities Integrating Electroactive Polymers Conductive Nanofillers and Flexible Electronics for Advanced Sensing and Actuation Systems
Abstract: Smart polymer composites have gained significant attention to their ability to integrate polymer matrices with conductive nanofillers, offering tunable electrical, mechanical, and electroactive properties. These composites are highly responsive to external stimuli such as electrical fields, mechanical stress, and temperature variations, making them ideal for applications in flexible electronics, soft robotics, and adaptive sensing systems. This research investigates the effect of nanofiller dispersion on the performance of polymer composites, optimizing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 946–965 Read article
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Advancements in Agricultural Forecasting: A Review of Machine Learning Based Crop Yield Prediction
Abstract: Agricultural productivity plays a critical role in global food security, and accurate crop yield prediction is essential for optimizing resource allocation and decision-making in farming. The rapid advancements in Machine Learning (ML) and Deep Learning(DL)have transformed agricultural forecasting, enabling data-driven approaches for crop prediction. This review paper provides a comprehensive analysis of various ML and DL techniques applied in crop yield forecast, highlighting the ineffectiveness, challenges, and future directions. The …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 32–38 Read article
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Enhancement of Digital Mammograms Using Intuitionistic Fuzzy Entropy Function
Abstract: A novel intuitionistic fuzzy entropy-based algorithm is developed for increasing the contrast of digital mammograms. The contrast enhancement helps in the early detection of masses and microcalcification in tissues thus paving the way for the auxiliary diagnosis of breast cancer. The current techniques for the enhancement of digital mammograms do not consider the uncertainty in pixel intensities of mammograms. The proposed technique aims at enhancing the mammograms using intuitionistic fuzzy …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 10, Issue 2, 2023 · pp. 10–26 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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Automated Brinjal Leaf Disease Detection Using Machine Learning: A Sri Lankan Study
Abstract: The spread of plant diseases has a significant negative impact on agricultural output quality and yield, resulting in significant economic losses. Plant disease automation in agricultural science is our country's main concern due to the economic crisis and the emphasis on organic farming practices. Furthermore, the accuracy and efficiency of recognizing sick leaves have increased due to the expanding usage of smart technology. This study uses machine learning and image …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 3, 2022 · pp. 41–56 Read article
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Renewable Solar Energy Prediction in India : 2025-2030
Abstract: As India endeavors to realize its objective of achieving 500 GW of renewable energy capacity by the year 2030, the precise forecasting of solar power generation is rendered increasingly essential. This scholarly article conducts a comprehensive review of the utilization of machine learning (ML) methodologies in the prediction of solar energy across diverse Indian states, underscoring their potential to address the complexities associated with the variability of solar irradiance. Conventional …
Published in Journal of Power Electronics and Power Systems · Vol. 14, Issue 3, 2024 · pp. 41–46 Read article
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Deep Learning -Based Dental Issue Detection
Abstract: Dentistry is vital for preserving oral health, a key component of overall wellness. Early identification of dental issues is crucial for effective treatment and avoiding further complications. Conventional approaches to diagnosing dental problems typically depend on physical examinations and visual assessments by skilled professionals, which can be both time-intensive and influenced by individual judgment.In recent years, the application of deep learning algorithms has demonstrated significant potential in automating and enhancing …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 1, 2025 · pp. 18–23 Read article
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AGRISMART: Crop and Soil Management System
Abstract: Agriculture has played a crucial role in developing countries where the majority of the rural population relies on it for their livelihoods. A finer-grade crop classification has become crucial in the context of precision agriculture. In recent years, the volume of open image data has grown significantly. This can be used in combination with machine learning techniques to classify crop types in the agricultural industry. The proposed crop species recognition …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 · pp. 50–55 Read article
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Brain Tumor Detection Using Image Processing
Abstract: Brain tumor means the aggregation of abnormal cells in some tissues of the brain. Brain tumor can be cancerous or noncancerous. The most common types of brain tumors are Glioma, Meningioma and Pituitary tumor. Early detection of tumor cells is essential in-patient treatment and recovery. A brain tumor is typically diagnosed through a lengthy and complicated process. The MRI images of various patients at various stages can be used for …
Published in Journal of Computer Technology & Applications · Vol. 13, Issue 2, 2022 · pp. 8–14 Read article
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Measuring Microstructure, Wear Resistance, and Mechanical Reliability Enhancement in Polymer Nanocomposites via Data-Driven Analysis with Deep Learning
Abstract: Polymer nanocomposites have gained great attention owing to their superior mechanical performance, better wear resistance and customizable microstructural properties for aerospace, automotive, medicinal and industrial engineering applications. However, the correct evaluation of the link between the microstructure evolution and the material reliability is a huge issue due to the intricacy of nanoscale interactions and diverse material characteristics. In this study, we propose a data-driven approach that integrates deep learning and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Prediction of Human Heart Disease
Abstract: AbstractData mining techniques have been widely used in clinical decision support systems for prediction and diagnosis of various diseases with good accuracy. These techniques have been very effective in designing clinical support systems because of their ability to discover hidden patterns and relationships in medical data. One of the most important applications of such systems is in diagnosis of heart diseases because it is one of the leading causes of …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 6, Issue 2, 2019 · pp. 27–31 Read article
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Noise-Removal Techniques for ECG Signals – A Survey Approach
Abstract: Modernization in medical sciences has led to the electrical signals vary according to the variation in the biological activities and abnormalities in the human body. ECG measures and records the electrical activity of the heart. Hence, the signals should be free from undesired signals to accurately analyze the abnormalities in the human body. Different techniques have been applied to make the ECG signal noise free. This paper presents a survey …
Published in Current Trends in Signal Processing · Vol. 3, Issue 3, 2013 · pp. 19–23 Read article