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798 articles for “deep learning”
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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 Review of AI-Based Intrusion Detection Systems for Mobile Ad Hoc Networks (MANETs)
Abstract: Mobile Ad Hoc Networks (MANETs) comprise wireless networks that lack any conventional infrastructure . Their chief features include highly changing network topologies, lack of centralized administration, and open nature of communication, which collectively result in making MANETs of the wireless kind very susceptible to a diverse range of cyber-attacks like blackhole, greyhole, wormhole, flooding, Sybil and denial-of-service (DoS) among others. Conventionally, Intrusion Detection Systems (IDS) relying on static rule-based methods …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Advancement of Lifelong Learning Through Online Communities
Abstract: The concept of long-lasting learning has risen with the development of web and e-learning. In today's competitive environment, learning is not restricted to a conventional four-year degree but is a progressing handle that endures all through the lifetime of a person. The Web offers curiously conceivable outcomes for dispersing instructive fabric to understudies, both locally and as portion of farther education. One of the vital parts of higher instruction in …
Published in Current Trends in Information Technology · Vol. 13, Issue 2, 2023 · pp. 9–17 Read article
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Harnessing Artificial Intelligence for Precision Physics: A Machine Learning Framework for Data Reconstruction in Support of India's Deep-Tech Missions
Abstract: India's emergence as a global leader in deep-tech innovation is driven by ambitious scientific megaprojects, including the Laser Interferometer Gravitational-Wave Observatory (LIGO)-India, the X-ray Polarimeter Satellite (XPoSat), the Aditya-L1 solar observatory, and the National Quantum Mission (NQM). However, the unprecedented scale and complexity of the observational data generated by these missions present severe computational bottlenecks. Traditional analytical frameworks struggle with non-stationary noise transients, diffusion blurring, and the exponential scaling limits …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 2, 2026 · pp. 48–55 Read article
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Methods for Asphalt Polymer Pavement Surface Monitoring: A Review
Abstract: Bitumen, also known as solid asphalt, is an intricate blend of organic molecules obtained during the distillation of crude oil. The chemical composition of it varies based on its origin, processing techniques, and intended use. Development in transportation sector led to increase the traffic volume in past year. Increase in the number of vehicles have tendency to deteriorate the pavement [paved or unpaved] surface due to heavy load and their …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 109–113 Read article
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AI-Driven Handwriting Identification and Verification Using Textural Features
Abstract: The last few decades have seen handwriting recognition and verification earn their mark in areas like forensics, healthcare, education, and digital security. This study delves into the role of artificial intelligence (AI), machine learning (ML), and deep learning techniques in handwriting analysis. It highlights the extraction of textural features as a precursor to identifying narrows between original handwriting and its forgery, whereby a few distinctive patterns such as stroke width, …
Published in International Journal of Electronics Automation · Vol. 3, Issue 1, 2025 · pp. 35–44 Read article
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Predicting Multiple Diseases Using Machine Learning: A Data-Driven Approach
Abstract: The increasing prevalence of chronic and life-threatening diseases highlights the need for innovative healthcare solutions that enable early detection and proactive management. The Multiple Disease Prediction Platform is a web-based system utilizing machine learning (ML) and deep learning (DL) algorithms to analyze user-inputted health data, generating real-time predictions of potential health risks. By leveraging Python’s Streamlit library, the platform provides an interactive and accessible diagnostic experience, eliminating the need for …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 16–35 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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The Early Brain Hemorrhage Prediction System Using Machine Learning
Abstract: Brain hemorrhage is a critical medical emergency that requires immediate attention, as delays in diagnosis can result in severe neurological damage or death. The condition involves bleeding within or around brain tissues, leading to increased intracranial pressure and disruption of normal brain function. Although imaging techniques such as CT scans and MRI provide accurate diagnosis, their availability is limited in emergency and rural settings. In recent years, machine learning has …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 Read article
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Optimized Sentiment Analysis Through TextBlob and Hybrid RNN Models
Abstract: In today’s world, analyzing people’s feelings from what they write online has become very important. This is because there is a large amount of content created by users. To make this analysis accurate and fast, we present a method. This method uses a mix of two approaches: one that looks up words in a dictionary and another that uses computer learning. TextBlob is an affordable tool for getting an initial …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 29–28 Read article
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Survey on Techniques to Segment Salt Bodies in Seismic Images
Abstract: The areas in the earth which are rich in oil and natural gas also have huge deposit of salt below the surface. So, it is very important for the hydrocarbon industries to acquire the needed resources. The important challenge of seismic imaging is to detect subsurface salt structure which is required for the identification of hydrocarbon reservoirs and drill path planning. Unfortunately, the accurate identification and classification of large salt …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 8, Issue 1, 2021 · pp. 25–30 Read article
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A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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Revolutionizing Knee Osteoarthritis Diagnosis: Unleashing the Potential of Vision Transformers
Abstract: Osteoarthritis (OA) is the most common kind of arthritis. By analysing data from both sides of the knee joints, radiologists use the Kellgren–Lawrence (KL) grading system to determine the severity of osteoarthritis (OA). The need for knee arthroplasties has increased as a result of this. Recently, there have been proposals for computer-assisted techniques to improve the precision of OA diagnosis. Choosing between conservative and surgical treatment options for knee osteoarthritis …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 1, 2024 · pp. 24–31 Read article
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A Robust Face Recognition Model based on Convolutional Neural Networks
Abstract: From the past several years, face recognition is one of the challenging issues in computer vision, due to three main technical problems in it. 1) Expression problem: in which same person shows more than one expression. 2) Illumination problem: in which face images of the person are strongly corrupted by lightning and 3) poses problem: in which large portion of the face becomes invisible due to occlusion. To this end …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 1, 2018 · pp. 1–11 Read article
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A Comparative Machine Learning Framework for Early Prediction of Liver Cancer Using Clinical Attributes
Abstract: One of the main causes of cancer-related death globally is liver cancer, and improving patient outcomes depends heavily on early detection. However, low contrast, noise, organ similarity, and tumor shape and size variability make it difficult to accurately identify and segment liver tumors from medical imaging. Automated liver cancer diagnosis, segmentation, and prognosis have been greatly improved by recent developments in artificial intelligence (AI), especially deep learning. This work presents …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 · pp. 39–47 Read article
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DeMe-Net Model to Diagnose Skin Cancer Disease from Skin Lesion
Abstract: Skin cancer is a quite common disease in the world and Melanoma is one of the serious types of skin cancer. It begins in melanocyte cells. Skin irritation or tanning due to UV radiation triggers changes in melanocytes, leading to uncontrolled growth of cells. It can potentially develop and spread if it is not treated early. The biopsy is a traditionally used method to diagnose skin cancer in which a …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 3, 2021 · pp. 10–20 Read article
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Breast Cancer Detection and Multiple Classification Using CNN
Abstract: Although some efforts have been made in the form of preventative screening programs, breast cancer remains one of the rising causes of death in women. Computer-assisted diagnosis is needed because of the rapidly increasing number of mammograms that can be collected by these programs. Performance metrics are not significantly improved by computer aided detection methods designed to improve diagnosis without a large number of sequential readings. In this context, self-imaging …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 12, Issue 2, 2023 · pp. 28–38 Read article
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A Comprehensive survey of robust image quality metrics for satellite imagery
Abstract: Satellite imagery is essential for applications like environmental monitoring, urban development, precision agriculture, defence surveillance, and disaster response. The reliability of these applications is closely tied to the quality of the captured images, which may be compromised by atmospheric effects, sensor imperfections, compression artifacts, and transmission noise. As a result, accurate image quality assessment (IQA) is essential to ensure trustworthy analysis and informed decision-making in satellite-based systems. The distinctive properties …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 1, 2026 · pp. 7–20 Read article
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A Voice Based Framework in Medical Emergency and Essential Services Using NLP (In Special Reference to People with Writing Disability)
Abstract: Natural Language Processing (NLP) has become increasingly popular in recent years as a means of organising and structuring knowledge for tasks such as translation, summarization, named entity recognition, relationship extraction, and audio recognition. The processing efficiency of NLP based systems has increased significantly with the introduction of deep learning algorithms. The COVID-19 pandemic has posed a challenge to medical research, information technology operations, corporate procedures, and the global economy. Several …
Published in Recent Trends in Programming languages · Vol. 9, Issue 2, 2022 · pp. 1–7 Read article
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Multinomial classification Identification for Domestic Violence Virtual Posts Based on Improved Convolution Neural Network (ICNN)
Abstract: AbstractDomestic violence isn’t only about the physical violence but further any conduct the purpose of which is to gain power and manage over a spouse, partner, girl/boyfriend or intimate own circle of family member which leads to the violation of human rights. Through the web-based networking media domestic violence crisis support (DVCS) have demonstrated fundamental help directions to abused people and their families. The unrivaled outcomes in online content description …
Published in Journal Of Network security · Vol. 8, Issue 3, 2020 · pp. 1–10 Read article