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235 articles for “Data Extraction”
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Transformative Breakthroughs: Revolutionizing Potato Disease Detection Through Machine Learning
Abstract: Advancements in agricultural technology and the integration of artificial intelligence for diagnosing plant and leaf diseases are crucial for sustainable agricultural development. Conditions like early blight and late blight exert a notable influence on both the quality and quantity of potato harvests. Identifying these leaf diseases manually demands significant labor and a considerable level of expertise. Therefore, efficient, and automated methods for disease detection are essential to improve potato production. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 54–62 Read article
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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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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 Knowledge Graph Approach for Breast Cancer Diagnosis and Data Sharing Platform Implementation in the Context of Human Papillomavirus Infection
Abstract: Background: Breast cancer remains among the most prevalent malignancies in women worldwide, and effective diagnosis and data integration continue to challenge clinical practice. Diagnostic reports from mammography and ultrasound contain rich clinical information that is often under-utilised due to heterogeneous formats and limited data-sharing infrastructure. In the context of human papillomavirus (HPV) infection, which may influence oncogenic pathways and data complexity, advanced computational methods offer new solutions to this problem. …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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Explainable GeoAI-Based Multi-Temporal Remote Sensing Framework for Early Detection of Climate-Induced Land Cover Transformation
Abstract: Climate change has emerged as one of the primary drivers of rapid land cover transformation, affecting ecosystems, agricultural productivity, biodiversity, and regional sustainability. Traditional remote sensing approaches often face challenges in detecting subtle and early-stage land cover changes due to limitations in temporal analysis and model interpretability. This study proposes an Explainable GeoAI-based multi-temporal remote sensing framework for the early detection of climate-induced land cover transformation using multi-source satellite imagery …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 2, 2026 Read article
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Innovative Approaches to Reducing Data Traffic in IoT Networks Using Deep Learning and Compressive Sensing
Abstract: The exponential growth of internet of things (IoT) devices has posed unprecedented challenges in managing the massive data generated by real-time monitoring, automation, and analytics. Existing network infrastructures lack scalability, bandwidth, and suffer from latency problems, further making data transmission less efficient. This study surveys innovative approaches using deep learning and compressive sensing to reduce IoT data traffic. Deep learning is able to upgrade data processing by means of very …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 46–62 Read article
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Advancements in Handwriting Recognition: A Deep Learning Approach
Abstract: This article provides detailed information about handwriting text recognition. Some human characteristics are unique to the individual. Writing is one of the scientifically proven habits that is different for everyone. Handwriting Text Recognition (HTR) is responsible for identifying written characters and converting them into digital text. HTR is an intensively researched area, but improvements can still be made in accuracy and efficiency. Digitization of manuscripts is very useful in today's …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 28–34 Read article
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Using Artificial Intelligence for The Design of Polymeric Drug Delivery Systems
Abstract: AI is cost effective and time efficient process. Artificial intelligence is a method which uses high speed calculation, the improvement regarding algorithm along with collection about biological and chemical features in pharmaceutical exploration and development .Present day because continuous progress towards machine learning (ML),Artificial intelligence an effective statistics analysing technology might have been broadly utilized in drug design .In pharmaceutical exploration and research employ of AI in target identification, compound …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1018–1027 Read article
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Mechanical Strength Prediction of Nano-Silica Concrete Composites Using Machine Learning Techniques
Abstract: Nano-silica, or nanosilica, refers to silicon dioxide nanoparticles, which are a kind of silica (SiO₂) with diameters that often fall below 100 nanometers. This nanomaterial has attracted considerable attention because of its distinctive characteristics and diverse array of uses, notably in augmenting the performance of materials such as concrete. The integration of nanoparticles with cementitious matrix in nano-silica concrete offers a viable approach to improving the mechanical characteristics and longevity …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 963–973 Read article
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A summary continuation analysis evaluating the prevalence and predictors of diabetic retinopathy in newly diagnosed type 2 diabetic patients.
Abstract: Context: Diabetic retinopathy (DR), the leading cause of acquired blindness in adults, affects approximately 93 million people globally. It is a serious complication of type 2 diabetes, resulting from prolonged damage to the blood vessels in the retina. Although largely preventable and treatable, DR continues to be the main cause of vision loss among working-age adults and significantly impacts quality of life. While most studies on DR in Nepal have …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 21–30 Read article
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AI Approaches in Gait and Posture Analysis: A Review
Abstract: This review synthesizes current research on the application of artificial intelligence (AI) in gait and posture analysis, focusing on methodologies, algorithms, and clinical applications. It examines the use of machine learning (ML) and deep learning (DL) techniques to extract relevant features from sensorderived data, offering objective, and automated assessments that surpass traditional methods. A systematic literature review was conducted, analyzing studies that utilized AI for gait and posture analysis with …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 1–3 Read article
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Power of Optical Sensors in Remote Sensing: A Study
Abstract: Imagine having eyes that could pierce the veil of the visible, discerning the subtle whispers of light beyond the spectrum our everyday vision allows. This isn't a superpower from science fiction, but the very essence of optical sensors in remote sensing – our planet's watchful, silent sentinels, meticulously translating the electromagnetic symphony into actionable insights. Optical sensors, operating within the visible, near-infrared, and short-wave infrared portions of the electromagnetic spectrum, …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 29–36 Read article
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Lightweight Models for Per-PC Energy Consumption Forecasting: Comparative Study with ML and DL Approaches
Abstract: We have collected primary data from automated logging of parameters like CPU utilization, estimated power, active or idle state, user logging activity, and the type of day. Additionally, survey data showed user awareness, energy-saving behaviour, and PC usage patterns. The data is pre-processed and merged by applying processes such as data cleaning, normalization, and feature extraction, i.e., determining the peak active timings and downtime. Developed lightweight prediction models based on …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 1, 2026 Read article
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Farmer Producer Organizations as Catalysts of Rural Transformation: A Multidimensional Framework from Punjab, India
Abstract: Farmer Producer Organizations (FPOs) have evolved as an important institutional mechanism for resolving the socio-economic challenges of small and marginal farmers by fostering collective action, expanding market access, and boosting bargaining power. In the broader context of sustainable rural development, FPOs are increasingly acknowledged as catalysts of rural transformation by contributing to numerous dimensions of farmer well-being. However, current study has generally analyzed FPOs through economic and operational indicators, with …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 3, 2026 Read article
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Fuzzy C-Means Clustering for Effective Segmentation and Classification of Brain Tumors in MRI Scans
Abstract: The paper discusses the importance of detecting and classifying brain tumors via MRI for effective treatment. It proposes a framework utilizing the Fuzzy C-means clustering algorithm for segmentation, demonstrating improved performance through real dataset validation. The model is trained on a large, annotated MRI dataset to identify and classify different tumor types, enabling machine learning-based classification into benign and malignant tumors. The MATLAB-based solution automates brain tumor feature extraction, aiding …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 23–28 Read article
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CNN-BILSTM Architectures for Handwritten Signature Verification: Insights and Innovations
Abstract: Verifying handwritten signatures is essential for identity authentication to guard against fraud and guarantee security across a range of platforms. The approaches and developments in handwritten signature verification are examined in this review, with an emphasis on both offline and online techniques. While online methods use dynamic information like stroke order and speed, collected by specialized devices, offline verification uses scanned photographs of signatures. Even if technology is moving toward …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 43–50 Read article
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Accelerate Drug Development with Pharmacokinetic Softwares
Abstract: During continuously evolving technologies and mechanized equipments, there has been a tremendous growth in the pharmaceutical sector over the past few decades. New technologies, software, devices, and techniques are being developed or researched upon with each passing day. By leveraging pharmacokinetic software, researchers can efficiently analyze vast datasets from preclinical and clinical studies, extracting actionable insights that inform decision-making early in the development cycle. This predictive capability not only accelerates …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
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Extraction, Isolation, Characterization of Curcumin-I From Curcuminoids
Abstract: The major goal of this study is to extract, isolate, and characterize curcumin-I, a component of curcuminoids. Turmeric, or Curcuma longa Linn., plays a significant role in Ayurvedic medicine. Turmeric, or Curcuma longa Linn, is the popular name for this plant. An array of chemicals with biological activity may be more easily extracted with the help of this seasoning. Some of the compounds at play include curcuminoids and turmerone, although …
Published in Journal of Polymer & Composites Read article
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Cutting- Edge Gravitational-Wave Detectors: Technology & Innovations
Abstract: Gravitational wave detectors using laser interferometry are sophisticated instruments designed to measure the ripples in spacetime caused by cosmic events such as the merging of black holes or neutron stars. This schematic outlines the fundamental components and working principle of a typical laser interferometric gravitational wave detector, such as those used in the LIGO and Virgo observatories. The core of the detector is an interferometer, typically a Michelson interferometer, with …
Published in International Journal of Universe · Vol. 1, Issue 1, 2025 Read article
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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