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513 articles for “deep network”
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A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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Early Lung Cancer Prediction using deep Learning
Abstract: Lung cancer is a global killer because it’s often found late. Finding it early is key to treatment and survival so computer assisted diagnostics are essential. This research uses deep learning to spot early stage lung cancer from CT scans. We trained and fine-tuned three convolutional neural networks—ResNet50, Dense Net 201 and EfficientNet-B0—using transfer learning. We preprocessed the lung CT images by resizing, normalizing and augmenting them to enhance the …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 Read article
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Path Planning using DDPG Algorithm and Univector Field Method for Intelligent Mobile Robot
Abstract: Path planning is one of the most fundamental challenging tasks in robotics and its purpose is to lead the robot from the initial position to the goal without any collision through the optimal route. With the rapid development of artificial intelligence technology, AI has been widely studied for robot path planning and a method by deep reinforcement learning (DRL) was proposed. In general, path planning methods with DRL need discrete …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 2, Issue 2, 2024 · pp. 1–9 Read article
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Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 45–54 Read article
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Machine Learning Based Optimization of Polymer Structure Property Relationships in Composite Material Systems
Abstract: In modern engineering applications, polymer-based composite materials have garnered a lot of attention because of their lightweight nature, high strength-to-weight ratio, and changing physical features. In order to maximize the relationships between polymer structure and properties in composite materials, this study suggests a strategy based on reinforcement learning (RL). The research utilized the Polymer Composite Properties Dataset, which contains 12,700 records associated with polymer matrices, reinforcement fillers, interfacial bonding characteristics, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 242–255 Read article
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An Efficient Secure and Security Authentication Scheme for Vehicular Ad-hoc Networks
Abstract: AbstractVehicular ad hoc networks (VANETs) are planned to be deployed within the next decennary to repair driver protection, stop clash, and provide traffic interpreter. Present years have supported an increasing interest in the security schemes for VANETs, as this territory was generally less investigated contrasted with different regions medium access and routing. In particular, efficient authentication of the messages in a VANET with other desirable security features has been heavily …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 5, Issue 1, 2018 · pp. 29–35 Read article
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Predicting Eye Blindness by Detecting Exudates in the Retina of Human Eye
Abstract: Diabetic retinopathy is a condition where a person suffering from diabetes starts to loosen his vision slowly as the severity of the disease increases gradually. We can diagnose this condition by the fundus image of the retina of the human eye; although it is very complicated for doctors to predict the conditions just by seeing the fundus images. By detecting diabetic retinopathy at the earliest, we can protect patients from …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 1, 2021 · pp. 17–23 Read article
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Decentralized Voting System Using Blockchain Technology
Abstract: Ethereum is a virtual currency that emerged in the aftermath of the financial crisis. It allows people to bypass banks and traditional payment processes to pay for goods and services. The technology on which ethereum works is of great interest to us. It is called the Blockchain. Blockchain is a continuously growing list of records, which are linked and secured using cryptographic methods. It allows its users the flexibility to …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 8, Issue 2, 2020 · pp. 15–20 Read article
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Heart Disease Diagnosis Using Artificial Neural Networks
Abstract: AbstractCoronary illness is a term covering any defect of the heart. In contrast to cardiovascular problem, which portrays issues with the veins and circulatory framework just as the heart, coronary illness alludes to issues and deformations in the heart itself. As indicated by the Centers for Disease Control (CDC), coronary illness is the main source of death in the United Kingdom, United States, Canada, and Australia. One of four passing’s …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 3, 2019 · pp. 32–36 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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A Survey Paper on Estimating the Online Social Networking Site
Abstract: A social network is a set of people or organizations or other social entities connected by set of social relationships such as friendship, co-working or information exchange. Estimating the server load of online social network sites is the most challenging research topic of the network management system. Also the online social web servers are existing in various countries. This Paper provides the necessary background on the online socialnetworking sites and …
Published in Journal of Web Engineering & Technology · Vol. 1, Issue 2, 2014 · pp. 9–15 Read article
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A Novel Deep CNN Model for COVID-19 Detection based on Lung CT Images
Abstract: In recent months, worldwide society has been destroyed by COVID-19 (Coronavirus Disease 2019), a catastrophic contagious illness that has ravaged the whole world. Deep learning (DL) approaches are the most widely used strategies for chest CT scan processing and illness prediction in the medical field. COVID-19 is infectious sickness that mostly influences the lungs also has the potential to be fatal if left untreated in its extreme form. It also …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 1, 2022 · pp. 1–14 Read article
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Oculight: AI Based System for Visual Assistance to Blind and Visually Impaired People
Abstract: This research introduces a new captioning model that utilizes both image and caption models to produce textual descriptions of images. By combining a convolutional neural network (CNN) and a long short-term memory (LSTM) recurrent neural network (RNN), this deep learning architecture offers a promising solution for improving the quality of life and independence of blind people through AIbased systems. The system's implementation on an Android device ensures that it is …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 22–29 Read article
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Data Maneuvering Identification
Abstract: Copy-move forgery detection (CMFD) is unquestionably one of the most active research areas in the field of blind image forensics. Most existing algorithms rely on block and key-point strategies, either separately or jointly. Recent applications of deep convolutional neural network (CNN) techniques include image forensics, image hashing retrieval, and picture classification. These techniques have outperformed more conventional techniques in many areas. In this study, a brand-new convolutional neural network based …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 99–104 Read article
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Network Intrusion Detection System Using Decision Tree
Abstract: This paper presents a novel approach to network intrusion detection systems (NIDS) using advanced decision tree algorithms to address critical limitations in existing IDS solutions. Traditional IDSs often struggle with high false positive and negative rates, lack of scalability, and poor interpretability. Our proposed IDS leverages decision trees to enhance detection accuracy, interpretability, and scalability, thereby improving network security. Decision trees are chosen for their adaptive learning capabilities, transparent decision-making …
Published in Journal Of Network security · Vol. 12, Issue 2, 2024 · pp. 22–33 Read article
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Enhancing Facial Recognition: Assessing CNNs for Detecting Image Manipulation
Abstract: Deepfake technology, powered by highly advanced deep learning models, has raised significant concerns regarding media manipulation, identity theft, and the spread of online disinformation. Due to the increasing sophistication of deepfake content, traditional forensic methods often fail to detect such artificially generated images with high accuracy. Consequently, deep learning-based approaches have become essential in combating this challenge. This study compares six prominent deep learning architectures: VGG16, ResNet50, MobileNetV2, InceptionV3, EfficientNetB0, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 27–36 Read article
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GreenDiagnosis: Intelligent Crop Disease Detection Using Deep Learning Algorithm
Abstract: Agriculture in parts of India relies on labour-intensive traditions, maintaining disease-free crops is crucial. Manual methods can be inaccurate, driving farmers towards AI-based solutions. AI offers a proactive approach to address real-time farming challenges. Among these is the invasion of pests, which diminishes crop quality. Combating pest-related diseases poses a challenge, prompting innovation. Effective surveillance and early detection of crop diseases play a pivotal role in ensuring global food security …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 Read article
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Survey Paper on Multilingual Live Call Translation Using Deep Learning
Abstract: This research work surveys cutting-edge language translation technologies, including multi-lingual, real-time translation, voice recognition, speech-to-text conversion, and transcription in the hearing process. The study explores the complex mechanisms behind voice call language translation, focusing on sophisticated machine learning models integrated with cloud-based or local applications to facilitate seamless communication across language barriers. Furthermore, conducting research in live communication analyzes the complexity of text and voice techniques to deliver translated content …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 2, 2024 · pp. 13–21 Read article
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A Review of Machine and Deep Learning Techniques for Cyber Security
Abstract: Nowadays in the digital landscape, cyber threats and attacks are increasing in an exponential manner, posing server risks to organizations and critical infrastructures. Data breaches often result from sophisticated threat models that exploit vulnerabilities in networks, systems and user behaviors. Cyber solutions are increasingly incorporating machine learning and deep learning to prevent and mitigate these security issues. These technologies have the potential to detect anomalies, classify threats and predict potential …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 01–07 Read article