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513 articles for “deep network”
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Computer based Automated Detection of Diabetic Retinopathy Stages using Neural Network
Abstract: Diabetic Retinopathy (DR) is a condition where a person suffering from diabetes for more than 10 years and has problem in vision. Due to DR, blood vessels in retina gets damaged. Patient also suffers from a blurred vision, finds difficulty in seeing colors in some cases or even total loss of vision. Retinal surgeries can relieve the symptoms, but efficient way to tackle DR is controlling diabetes and managing early …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 7, Issue 2, 2020 · pp. 13–17 Read article
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Review of Control Strategies in Lower Extremity Exoskeleton
Abstract: Personal mobility is one of the biggest challenges for ensuring the quality of rehabilitation in the lives of Persons with Locomotor Disabilities (PwLDs) and old aged persons. In order to ensure effective orthotic rehabilitation, there is need to design and develop more and more automated aids and appliances. In order to know the status of research a study has been made on the controllers of lower limb exoskeleton (LLE). In …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 1, Issue 2, 2023 · pp. 9–21 Read article
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Data Handling Algorithms for the Healthcare System for the Prediction of Diabetes in Health Data Science (HDS): A Review Report
Abstract: In recent years, diabetes has become the biggest disease in different countries around the world. This disease is caused by adulteration in food ingredients, unhealthy food habits, a lack of physical exercise, and changing the lifestyle every time without a routine chart. The main objective of this review paper is to provide a proper understanding of the machine learning algorithm used in the healthcare system to handle diabetic patients' data. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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AI-Driven Psychological Profiling on Social Media: Mechanisms, Ethical Breaches, and Regulatory Challenges in Data Inference
Abstract: This literature review examines AI-driven psychological profiling on social media, analyzing 21 academic studies that focus on machine learning techniques such as supervised learning, deep neural networks, sentiment analysis, and natural language processing. These methodologies infer mental health indicators—such as depression, anxiety, and stress—from users' digital footprints, encompassing linguistic patterns, engagement metrics, and temporal behaviors. While these tools offer potential for early detection of psychological distress, they also raise significant …
Published in Recent Trends in Social Studies · Vol. 2, Issue 1, 2025 · pp. 1–7 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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AI-Assisted Optimization of Supersonic Airfoil Shapes Using CFD Coupling
Abstract: This paper presents a novel framework for optimizing supersonic airfoil geometries through integrated artificial intelligence and computational fluid dynamics coupling. Traditional gradient-based optimization methods for high-speed aerodynamic shapes suffer from computational expense and convergence difficulties in non-convex design spaces. The proposed methodology employs a deep neural network surrogate model trained on high-fidelity Reynolds-Averaged Navier-Stokes solutions to approximate aerodynamic performance metrics across the design space. A hybrid particle swarm-genetic algorithm searches …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 8–17 Read article
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Multi-Scale Analysis of Polymer Based Energy Storage Systems for High Performance Battery Applications
Abstract: The energy storage systems based on polymers are becoming promising materials for the next generation of high performance batteries because of their excellent mechanical flexibility, improved safety, and favorable electrochemical properties. Even with computational tools in Python, polymer-based energy storage systems remain plagued by poor ionic conductivity, complicated electrochemical reactions and potential thermal runaway. Therefore, a multi-scale model is proposed to improve battery performance, thermal stability, reliability, and large-scale deployment …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1035–1048 Read article
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A Comprehensive Survey of Polymer Detection Techniques and Computer-Based Analysis Methods for Advanced Material Characterization
Abstract: Polymers are widely used in aerospace, automotive, biomedical, packaging, electronics, and manufacturing industries because of their lightweight nature, durability, and versatility. Accurate polymer identification and characterization are essential for quality control, recycling, performance assessment, and the development of advanced materials. Characterization helps determine important properties such as chemical composition, molecular structure, thermal stability, mechanical strength, and surface morphology, which influence material performance and application suitability. Traditional polymer detection methods include …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 921–929 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Wind Speed Forecasting
Abstract: AbstractAs the world exhausts its non-renewable energy reservoirs, building predictive models for renewable energy dependencies comes important a fortiori. In this study we examine how well a Deep Neutral Networks performs on wind speed data in a time series forecasting. The data used are based on wind speed readings acquired at the first-of-its-kind LiDAR based offshore which is situated at the Gulf of Khambhat, Gujarat, which is about 23 km …
Published in Recent Trends in Electronics Communication Systems · Vol. 7, Issue 2, 2020 · pp. 13–17 Read article
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Face Mask Detection Alert System
Abstract: The COVID-19 coronavirus epidemic is widely spreading around the world, which is why wearing face masks in public is becoming more popular. Since the WHO has made wearing masks mandatory to prevent this deadly virus, wearing face masks regularly is an essential measure until the virus is completely eradicated. Several preventive measures are being considered to decrease the spread of disease and one of them is wearing masks in crowded …
Published in Recent Trends in Sensor Research & Technology · Vol. 9, Issue 2, 2022 · pp. 25–31 Read article
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Native Language Identification from Spoken Indian English
Abstract: Automatic speech recognition (ASR) systems that facilitate voice based search and information retrieval have gained importance recently. While the performance of ASR systems for Indian languages have improved in the recent past. They have yet to gain wide acceptability as much as the ASR systems for English spoken by Indians. Almost all Indians learn English as a second or third language. So, the phoneme set and the prosody of native …
Published in Trends in Electrical Engineering · Vol. 9, Issue 2, 2019 · pp. 1–6 Read article
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AI Robotic System in Medical Field
Abstract: Our idea focuses on implementing a robot equipped with a special Artificial Intelligence Program (AIP) for performing surgery in the medical field and various other medical operations. The special AI program is made of deep neural networks, which is trained for thousands of medical prescription and surgical operations procedures. As the AI program is highly trained program the error rate will be almost negligible as compared to the error rates …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 6, Issue 1, 2017 · pp. 20–26 Read article
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Adaptive and Explainable ML Framework for Personalized E-Commerce User Experience and Satisfaction
Abstract: The user experience and user satisfaction have taken the center of the stage as a determinant of platform success in the fast-changing e-commerce ecosystem. Conventional recommendation systems are usually run in black-box models that give minimal transparency and dynamicity to altered user preferences. The study will introduce a personalization framework of explainable machine learning (XML) based on explainable artificial intelligence (XAI) and hybrid recommendation strategies. The model uses Collaborative Filtering …
Published in Current Trends in Information Technology · Vol. 16, Issue 2, 2025 · pp. 23–32 Read article
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Cascade CNN Framework for Low Resolution Image Classification
Abstract: Abstract: Low resolution images contain less visual information, so classifications of these images are difficult. For overcoming this problem, cascade CNN framework for low resolution image classification is proposed. In this framework, super resolution CNN (SRCNN) enlarges low resolution image into super resolution image. The convolutional features of these super resolution images are fused with low resolution convolutional features which are extracted by low resolution CNN (LRCNN) feature extractor. A …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 1, 2019 · pp. 39–43 Read article
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Vegetation Classification Based on Leaf Pattern
Abstract: In this current world, vital species of plants are going to be lost day by day. To command, this phenomenon, steps are first discovering then restoring and retain them. Among them, spotting of plant is giving up challenging. Usually, plants are recognizing from their leaves. In this paper, a deep neural network model is implemented which will extract the hidden pattern form leaf images. A classifier named as Convolutional Neural …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 8, Issue 3, 2021 · pp. 9–16 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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Diminution of Co-channel Interference in Femtocell Networks
Abstract: In the field of telecommunications, a femtocell is defined as a low-power cellular base station that is typically designed for use in a home or small business. A broader term which is more widespread in the industry is small cell, with femtocell as a subset. It acts as a service provider that allows to extend service coverage indoors or at the cell edge, especially where access would otherwise be limited …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 1, Issue 1, 2014 · pp. 24–30 Read article
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Automatic Car Controller Based on Sign Board using Deep Learning and IOT
Abstract: The rapid growth of intelligent transportation systems has increased the demand for safer and more efficient driving solutions. Conventional vehicles often rely heavily on human intervention, which can lead to accidents due to negligence, fatigue, or poor visibility of traffic signs. This project proposes an automated car control system that utilizes deep learning and Internet of Things (IoT) technologies to recognize traffic signboards and respond accordingly. The primary objective is …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 2, 2026 · pp. 16–24 Read article
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Real-Time Gesture Recognition with Convolutional Neural Networks
Abstract: Sign language detection plays a pivotal role in bridging communication barriers for the deaf and hard of hearing community. An extensive investigation on the use of convolutional neural networks (CNNs) for sign language recognition is presented in this article. Leveraging the power of deep learning, our research aims to develop an accurate and efficient system capable of recognizing and classifying sign language gestures in real-time. The report begins with an …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 2, 2024 · pp. 12–18 Read article