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412 articles for “Neural Network Techniques”
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Machine Learning-Based Disease Prediction: A Comparative Analysis for Diabetes, Brain Tumor, and Parkinson's Disease
Abstract: This paper presents a web-based disease prediction system that integrates machine learning and deep learning techniques to assist in the early detection of Parkinson’s Disease, Diabetes, and Brain Tumors. By utilizing clinical data and MRI images, the platform provides rapid and interpretable predictions to support proactive health management. Logistic Regression models are applied to classify structured datasets for predicting Parkinson’s disease and Diabetes, making use of their effectiveness in binary …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 44–54 Read article
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A Technical Blueprint for AI-Driven Localization in 6G Mobile Networks
Abstract: The advent of sixth-generation (6G) wireless systems promises unprecedented spatial resolution, ultra-low-latency, and pervasive connectivity, turning mobile localization from a peripheral service into a core enabler of immersive extended reality (XR), autonomous logistics, and digital twins. Yet, the sheer scale of dense terahertz (THz) deployments, the stochastic nature of reconfigurable intelligent surfaces (RIS), and the dynamic interference landscape render traditional model-based positioning techniques inadequate. This work investigates how artificial intelligence …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 26–34 Read article
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BREAKDOWN VOLTAGE TEST OF DIFFERENT SOLID INSULATING MATERIALS USING ARTIFICIAL NEURAL NETWORK MODEL
Abstract: In this paper we are presenting Artificial Neural Network (MFNN) model which has different possible inputs affecting the breakdown voltage that are working temperature, the insulating material thickness, dielectric strength of insulating material, volume resistivity of materials, dissipation factor, conductivity of materials, and the materials relative permittivity that also predicts the breakdown voltage as a function of all these inputs parameters. It is important to train the Artificial Neural Network …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 6, Issue 2, 2018 · pp. 22–29 Read article
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Intrinsic Evaluation of Graph Embeddings: Assessing Clustering and Community Detection Performance
Abstract: This paper presents an intrinsic evaluation of some graph embedding techniques on clustering and community detection tasks. We analyze a diverse set of embedding methods, ranging from traditional techniques such as Laplacian eigenmaps to more recent approaches like graph autoencoders, high-order proximity preserved embedding (HOPE), and graph attention network (GAT), using two widely studied datasets, Cora and CiteSeer. Our evaluation relies on two main metrics: Silhouette score with respect to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 40–48 Read article
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Performance Analysis of Fusion Classifier of Face Recognition System based on ANN and GA
Abstract: Though a lot of significant work has been done for recognizing and improving the performance in facial pattern, most techniques have been developed based on a single classifier. But most often, the performance of the classifier is not satisfactory in some case. It has been proposed that the performance of face recognition will beimproved by fusing two or more classifiers. We can combine the information/data in different level i.e., feature …
Published in Current Trends in Information Technology · Vol. 4, Issue 1, 2014 · pp. 4–13 Read article
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Examining the Crowd in Real-time with Deep Learning
Abstract: In this research, a model is proposed that can be used to estimate crowd density in a specific region and to establish social distances in accordance with predetermined rules. This is accomplished utilizing a multi-source model-based approach. In a small public gathering where hand counting is impossible, this technique conducts a survey. To do this, input video frames are extracted, each frame is processed, and then passed to the model …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 1, 2023 · pp. 41–45 Read article
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Advanced Helmet Recognition System with Integrated Number Plate Detection for Enhanced Traffic Monitoring Using Deep Learning
Abstract: This study focuses on the crucial problem of non-adherence to traffic regulations, particularly with the compulsory use of helmets by motorcyclists. Motorcycle accidents have a greater mortality rate compared to other types of accidents, indicating a need for a more effective enforcement strategy. Current procedures depend on traditional techniques where traffic officers manually observe traffic rule infractions through patrols and monitoring CCTVs, requiring substantial labor and time resources. The inherent …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 1, 2024 · pp. 9–18 Read article
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Multivariant Disease Detection from Different Plant Leaves and Classification
Abstract: Agricultural growth is significant in Indian GDP which is based on yield of crops, quality of the plants and procedure of the plants taken. To maintain good quality of plant, the plant diseases should be identified and then given proper suggestions to farmers for specific fertilizers and pesticides to be used. The use of specific fertilizers or pesticides makes plant more health with good quality so that farmers can get …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 27–35 Read article
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Artificial Intelligence for Automatic Load Management
Abstract: Demand-side management (DSM) means the load or consumer side management of electric energy for the optimum efficiency of the power system. DSM helps the electric utility by satisfying the requirements of a larger number of consumers with the existing generation capability and it also decreases the requirement for new generation capacity. Demand side management programs can be of great use to the electrical utilities as they eradicate the need to …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 3, 2021 · pp. 1–9 Read article
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Robust Classification of Traffic Signs Using Relief Feature Reduction Technique
Abstract: Ensuring driver safety amidst the rapid growth of global population and vehicular density continues to be a paramount challenge for transportation authorities and governments worldwide. With the rise of smart mobility solutions and autonomous driving technologies, the ability to detect, classify, and respond to traffic signs accurately has become critically important, especially under diverse and adverse environmental conditions such as rain, fog, or poor lighting. Reliable traffic sign recognition not …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 30–37 Read article
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Using Machine Learning to Guess Photochemical Reaction Pathways
Abstract: Photochemical reactions are crucial to many activities in the fields of energy conversion, environmental cleanup, and synthetic chemistry. However, predicting their causes and results effectively is still very hard since they entail excited electronic states, nonadiabatic transitions, and complicated potential energy surfaces. Machine learning (ML) has been a powerful technique to go along with classic quantum chemistry methods in the last few years. It offers better prediction capability and lower …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 01–12 Read article
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Retinal Disease Detection Using Deep CNN
Abstract: Age-related macular degeneration, glaucoma, and diabetic retinopathy are the three main causes of blindness in the globe. To avoid visual loss, early identification and treatment of these disorders are essential. The goal of this research is to create an automated method for detecting retinal diseases by analyzing retinal fundus pictures with machine learning techniques. Python and the Tkinter package for the graphical user interface are used in the construction of …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 46–50 Read article
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Innovative Eyewear for the Visually Impaired
Abstract: Object detection systems are essential tools for identifying and locating objects within images or videos. When integrated into spectacles or wearable devices, these systems provide users with real-time information about objects present in their surroundings. This functionality serves diverse purposes, such as assisting visually impaired individuals in navigating their environment or offering augmented reality data to workers during tasks. Region-based Convolutional Neural Networks (RCNN) represent a prominent machine learning model …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 1, 2024 · pp. 27–34 Read article
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AI-Driven Optimization of Biopolymer Composite Formulations Using IoT Data Streams
Abstract: Biodegradable polymer composites have emerged as a sustainable alternative to petroleum-based materials in packaging, biomedical, and structural applications. However, traditional formulation techniques for reinforced polymer composites often lack precision and fail to adapt to real-time variations during processing, resulting in suboptimal material performance. This research proposes a real-time AI-IoT-enabled framework to optimize biopolymer composite formulations. The goal is to intelligently tune composite properties such as mechanical strength, moisture resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 85–100 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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Artificial Neural Network Implementation in FPGA using Multiplexer-based Weight Updating for Efficient Resource Utilization
Abstract: This paper presents a novel scheme for field-programmable gate array (FPGA) implementation of an artificial neural network (ANN). The proposed implementation is aimed at reducing resource requirement, without compromising on the speed so that a complex ANN architecture could be realized on a single chip at a lower cost. The weight updating process in different layers of the ANN has been carried using a simple MUX-based architecture. Backpropagation algorithm which …
Published in Journal of Semiconductor Devices and Circuits · Vol. 2, Issue 1, 2015 · pp. 1–5 Read article
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Timely Diabetes Possibility Prediction Using AI Techniques
Abstract: The fastest chronic life-threatening disease affecting more than 422 million people globally is diabetes. The primary causes of type 2 diabetes are lifestyle choices and environmental factors. It is a slowgrowing disease which starts to develop metabolic factors long before they evolve into a disease and is formally diagnosed by a fasting sugar test. There are records of indications related to diabetes from 520 patients in the dataset that was …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 2, 2022 · pp. 37–47 Read article
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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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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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A Review on AI Driven IoT Based Decision Making in Rainfall Perdition in Climate Change Study
Abstract: We are moving from a reactive relationship with the weather to a symbiotic one. This AI-IoT framework is more than just a technological upgrade; it is a vital adaptation strategy in an age of climate volatility. As climate change induces unprecedented volatility in global weather patterns, traditional meteorological forecasting models often struggle to maintain hyper-local accuracy. This paper explores the convergence of the Internet of Things (IoT) and Artificial Intelligence …
Published in International Journal of Climate Conditions · Vol. 3, Issue 2, 2026 · pp. 1–6 Read article