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513 articles for “deep network”
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Performance Analysis of Deep CNN Architectures
Abstract: A Convolutional Neural Network (CNN) is an artificial neural network renowned for its remarkable ability to handle large image datasets effectively, particularly excelling in tasks such as image recognition and classification. The fundamental structure of a CNN relies on mathematical convolution operations, comprising essential components such as convolutional layers, activation functions, pooling layers, and fully connected layers. These components work synergistically to extract and learn hierarchical features from input data, …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Smart Diagnosis Using Machine Learning
Abstract: We discuss a plausible way for smart diagnosis. Theuse of Deep Learning in image processing can enable us to build Models to detect the presence of ailments in Diagnostic Images such as X-Ray or CT Scans performing as a diagnosis tool. These trained models can be effortlessly added into an easily accessible portal like a website or a phone application providing ease of use even for a non-practitioner. Further, we …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 2, 2020 · pp. 39–45 Read article
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Data Security System for a Bank using Hybrid Algorithm
Abstract: A secure security system is critical for a secure banking system. A secure banking system is required to prevent the theft of sensitive data from banks and clients. In today's world, exchanging vital information over the internet is extremely simple and quick. The easier it is to exchange information, the easier it is for the hacker to steal our information .As a result, a strong security system is required. To …
Published in Journal of Electronic Design Technology · Vol. 14, Issue 2, 2023 · pp. 25–36 Read article
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Detection and Classification of Brain Tumor from MRI And CT Images using Harmony Search Optimization and Deep Learning
Abstract: Primary brain tumor detection and classification are critical factors in ensuring effective treatment and, ultimately, improving patient well-being. This paper describes a novel method for detecting and classifying brain tumors with the help of magnetic resonance imaging (MRI) and computed tomography (CT) images. The suggested method combines harmony search optimization (HSO) and Convolution Neural Networks (CNN) based on deep learning techniques, yielding an impressive accuracy rate of 99.13% for both …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 31–49 Read article
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Intelligent Failure Detection in Biomedical Composite Materials Using Machine Vision
Abstract: The biomedical composite materials are intelligent failure-detecting, which is necessary to ensure the reliability, safety, and durability of the current healthcare equipment. This paper describes a machine vision design, which incorporates convolutional neural networks, transformer models, and ensemble learning to correctly detect and localize material defects. The proposed system takes advantage of the capabilities of high-resolution imaging, advanced preprocessing software, and deep feature learning in the identification of the intricate …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Design and Development of Agrobot Using Feed Forward Network for Smart Farming Agriculture
Abstract: The Agrobot framework is a form of natural language processing that requires training to understand human language and meet user needs accordingly. The development of a chatbot tailored for the agricultural industry represents a significant advancement in agricultural technology. This chatbot serves as an interactive tool to assist farmers in various aspects of agricultural practices, including crop management, pest control, weather forecasting, and market information. The main objective of this …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 1, 2024 · pp. 6–14 Read article
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An Analysis of Graph Database in Data Modelling and Analysis for a Recommendation System
Abstract: This research work focuses on graph databases, mainly Neo4j databases, in recommendation systems for e-commerce websites. The importance of research is that it explains how graph databases efficiently handle the complex relationship between user-items, which is difficult for traditional databases. Sparsity, limited diversity, and high setup costs are the challenges traditional databases face. This research work overcomes these problems using Ne04j with Cypher query language and graph algorithms (PageRank, Shortest …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 33–39 Read article
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A Neuromorphic-Inspired, Low-Power VLSI Architecture for Edge AI in IoT Sensor Nodes
Abstract: As the proliferation of Internet of Things (IoT) devices continues to rise, there is an increasing demand for real-time, energy-efficient artificial intelligence (AI) processing directly at the network edge. Traditional edge AI accelerators, often based on deep learning models like convolutional neural networks (CNNs), struggle to meet the ultra-low-power requirements of battery-constrained IoT sensor nodes. In response to this challenge, this study introduces a neuromorphic-inspired, low-power very- large-scale integration (VLSI) …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 41–47 Read article
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Wideband Ring Dielectric Resonator Antenna Using C Shaped Parasitic Elements
Abstract: Abstract: This paper presents a Ring Dielectric Resonator Antenna for wideband applications. Ring DRA is excited by annular shaped microstrip feedline. Bandwidth enhancement is achieved by adding the C-shaped parasitic elements on both sides of ring dielectric resonator antenna and removing the central part of a cylindrical DRA to form ring DRA. The operating frequency of proposed DRA lies between 2.054–6.5 GHz. Gain and Radiation efficiency of this proposed antenna …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 6, Issue 1, 2019 · pp. 32–37 Read article
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Prostate Cancer Detection Using Deep Learning
Abstract: Prostate Cancer is a cancer occurs in prostate gland which is located in male reproductive system. According to the WHO (World Health Organization) the estimated cancer cases in the year 2020 is about 1.4 Million. Prostate cancer is one of the reason for death in men. In this paper we have presented Secondary verification tool for doctors or for normal users to check patient have a cancer or not. And …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 2, 2023 · pp. 21–26 Read article
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Medical Applications of Artificial Neural Network
Abstract: The correspondence between the natural neurons and artificial neurons is defined in this paper. Thus, an excellent idea appears to design the standard diagnosis key diagnosis systems, which security is based on the well known number theoretic problem, i.e. elliptic curve discrete logarithm problem in multiplicative group of the finite field. But now we are moving in the revolutionary idea, “The Automatic groups G converted into the multiplicative groups G’ …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 7, Issue 2, 2020 · pp. 23–30 Read article
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Evaluation of composite material based on different phases of Face recognition System
Abstract: Composite materials can indeed play a crucial role in various phases of a face recognition system, offering advantages such as lightweight construction, durability, and tailored mechanical properties. Let's explore how composite materials can be utilized in different phases of a face recognition system. A composite material based different phases of Face recognitions System is software that recognizes or verifies a person based on a digital image or a frame from …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 195–204 Read article
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Intelligent Brain Tumor Diagnosis with AI-Based Classification* * Harnessing Deep and Machine Learning for Tumor Identification
Abstract: Brain tumors have become a leading cause of cancer- related deaths, posing significant health risks to many patients. This urgent medical challenge calls for rapid, automated, and reliable techniques to detect brain tumors accurately. Timely and precise tumor identification is crucial for devising effective medical plans that have the potential to save lives and improve patient outcomes. By leveraging advanced image processing methods, healthcare professionals can enhance their diagnostic capabilities …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 1, 2026 · pp. 51–58 Read article
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An Analytical Review of Machine Learning Methodologies
Abstract: Machine Learning (ML) is a dynamic and rapidly developing area of computer science that enables the system to learn from data and improve its performance without clear programs. Rooted in statistical theory and computer algorithms, ML has become a major technology that progresses in artificial intelligence. It strengthens the detection of the recommendations and speech for extensive applications from autonomous vehicles and medical diagnoses. This paper has reviewed the basics …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 13–21 Read article
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Modified Binary Firefly Algorithm (MBFA) for Optimal Allocation of Spectrum in Cognitive Radio Systems
Abstract: Spectrum bands are nature’s communication highways which are highly congested now-adays. To overcome this problem, dynamic allocation of spectrum is under consideration over the current fixed spectrum allotment policy. In dynamic allotment, various optimisation methods can be applied for achieving the best possible spectrum allotment during handover so that the better quality of service can be given to cognitive users with the simultaneous improvement in spectrum utilisation. This study focuses …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 3, Issue 2, 2016 · pp. 42–47 Read article
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Relay Node Selection Based Reduced Energy Consumption in Heterogeneous Wireless Sensor Network
Abstract: Energy conserving optimization is of chief concern while scheming a wireless sensor network (WSN) as most of the sensor nodes are furnished with limited power supply. In this paper, we focus on minimizing energy consumption and maximizing network lifetime in three-tiered network architecture. For this obvious goal, clustering techniques are a boon with a hierarchical arrangement to boost the performance of the network as well as reduce the consumption of …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 3, Issue 2, 2016 · pp. 7–14 Read article
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An Overview of Artificial Neural Network and its Applications
Abstract: This paper presents an overview of Artificial Neural Network (ANN). The study of neurons and its discrete representation by the set theory is the key objective of this paper. New data structure technique is proposed in this paper by using the mechanism of (ANN). The finite dimension of the field is generalized in this paper. The linear transformation and the representation of the vector basis are applied to propose the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 2, 2020 · pp. 17–20 Read article
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Detection of Pneumonia in COVID-19 Patients Using X-ray Images
Abstract: This study explores the use of chest X-ray image analysis and deep learning methods to identify pneumonia in COVID-19 patients. Due to the pandemic, Proper as well as immediate examination of COVID-19 is now essential for patient care and disease control. This study proposes a novel approach that uses convolutional neural networks (CNNs) to automatically predict pneumonia in COVID-19 patients using chest X-ray images. In this study, an X-ray of …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 13–23 Read article
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Empowering Healthcare Through IoMT: Unveiling the Architecture, Protocols, and Applications
Abstract: The "Internet of Things" (IoT) is the infrastructure of web-connected devices that automatically gather and transport data through a remote network. Due to the rapid growth of IoT-based gadgets and their expansion towards making medical care facilities financially smart, proactive, and customizable, the "Internet of Medical Things (IoMT)" is presumed proactive in all areas of healthcare. Using cutting-edge technology, the IoMT-based healthcare system offers rapid and reliable treatment, increased communication, …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 10, Issue 2, 2023 · pp. 10–23 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