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334 articles for “feature based model”
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Agile Modeling and Building an Inclusive Online Coding Platform for Programming
Abstract: The integration of agile modeling principles within professional programming emphasizes the development of online coding platforms tailored to meet the diverse needs of computer science and engineering students. This study introduces an agile-based, API-integrated J2EE online coding platform, designed to create a sophisticated and user-friendly environment for seamless programming practice, particularly focusing on Java programming. The platform offers real-time tracking of programming progress and enhances the understanding of complex coding …
Published in Recent Trends in Programming languages · Vol. 11, Issue 2, 2024 · pp. 33–42 Read article
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Recent Advances in Content-based Image Retrieval: Techniques and Applications
Abstract: Content-based image retrieval (CBIR) plays a vital role in computer vision, driven by the increasing need for fast and accurate image retrieval across fields like healthcare, e-commerce, and digital libraries. This study offers a detailed review of CBIR methodologies, charting their progression from traditional feature extraction techniques, such as Local Binary Patterns (LBP), to contemporary deep learning-driven methods. The transformative impact of convolution neural networks (CNNs) is highlighted, emphasizing their …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 67–71 Read article
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FRW Universe in R2 Gravity
Abstract: We investigate a model of the Friedmann Robertson Walker metric (FRW) universe governed by hybrid expansion law (HEL) a = tα eβt in R2 gravity. By Applying, energy and stability conditions in derived model, we check its physical viability. This model is based on f (R, T) = f (R) + f (T); f (R) = R + αR2 and f (T) = T and we have assumed T = …
Published in Journal of Polymer & Composites · Vol. 11, Issue 7, 2023 · pp. 75–80 Read article
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Fractal-Entropy Guided Adaptive Signal Reconstruction for Non-Stationary Biomedical and Communication Systems
Abstract: This paper presents a novel Fractal-Entropy Guided Adaptive Signal Reconstruction (FEG- ASR) framework designed for accurate processing of non-stationary signals in biomedical and communication systems. The proposed approach integrates fractal dimension analysis with entropy- based feature evaluation to capture the intrinsic complexity and irregularity of time-varying signals. By dynamically adapting reconstruction parameters based on fractal-entropy measures, the method effectively separates noise from meaningful signal components while preserving critical information. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 · pp. 22–33 Read article
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Nail Image Processing for Early Symptom Detection of Diseases based on Supervised Learning
Abstract: Digital Image Processing of human nail can be used for the prediction of various systemic and dermatological diseases. The proposed system – Nail Image Processing System using SVM (NIPS-S) helps us to create a model for the analysis of human nail and predict various diseases. The input to the proposed system is the Human Palm Image. The nail portion is segmented and a combination of nail color, shape and texture …
Published in Journal of Computer Technology & Applications · Vol. 8, Issue 3, 2017 · pp. 49–61 Read article
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A Comparative Study of Statistical Features for Satellite Images with Natural Images
Abstract: While satellite imaging involves several bands that capture the geographical features, the natural images taken from camera in real world uses RGB model, which is composed of three channels, where each image can store discrete pixels with conventional brightness intensities between 0 and 255. So, the uniqueness of the two imaging techniques is reflected in its bits of every pixel. It is well known that the whole information of an …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 2, 2016 · pp. 59–66 Read article
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Violent Event Recognition and Monitoring Using Deep Learning for Surveillance Videos
Abstract: The significance of real-time capabilities in human detection and tracking is discussed in the abstract of the paper. We talk about tracking, eye detection, and face detection. A thorough motion detection program for use in video monitoring and other applications is suggested by the study. The goal of the study is to further human tracking technology. Optical flow features and appearance-invariant features from a Darknet CNN model are integrated. Acquiring …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 1, Issue 2, 2023 · pp. 39–44 Read article
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Convolutional Neural Network Based Ripeness Detection of Fruits
Abstract: The accurate and efficient assessment of fruit ripeness plays a crucial role in ensuring the quality of fruits and optimizing supply chain management. This paper presents a novel approach for the automated detection of apple and banana ripeness using Convolutional Neural Networks (CNNs). The suggested method supports the capability of CNNs to learn hierarchical features from images, variations in color and shape associated with different ripeness stages. The online dataset …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 13, Issue 2, 2024 · pp. 30–36 Read article
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Detection of Phishing Website Using URL
Abstract: Phishing attacks are one of the greatest threats to online security, where fraud websites deceive users into giving out sensitive information. Traditional methods of detection, such as blacklists and heuristic-based systems, often fail in identifying newly created or sophisticated phishing websites. This study proposes an intelligent phishing website detection system using Convolutional Neural Networks (CNNs) in analyzing URLs and associated features. Using labeled URLs, the system employs such attributes such …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 10–15 Read article
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Sustainable Cotton Crop Productivity through Precision Weed Detection: A Deep Learning-Based Approach with UAV Integration
Abstract: Weeds present a major challenge to crop productivity by competing with crops for vital resources, including water, sunlight, and nutrients, often resulting in significant yield reductions. On a global scale, weeds are responsible for approximately 13.2% of annual crop losses, a quantity sufficient to feed nearly one billion people. These invasive plants disrupt agricultural systems and adversely impact crop yields. Given their uneven distribution in fields, ground or aerial robots …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 19–26 Read article
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Music Recommendation System and Mood Tweak Using Facial Emotion Recognition
Abstract: A user’s emotions can be detected through their facial expressions, these characteristics can be parsed, and the information can be used to improve the user’s experience. With the computing capabilities of on-board graphic processing, there is a new trend of functionality being considered in the field of emotion detection. The use of Convolutional and Recurring Neural Networks (CNN & RNN) to conduct a comparison on which deep learning can be …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 1, 2022 · pp. 43–49 Read article
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Automated Machine Learning System for Model Selection and Hyperparameter Optimization
Abstract: The proliferation of machine learning applications in various scientific and industrial domains has given rise to an urgent need for developing principled, automated techniques for optimal architecture selection and hyperparameter tuning for machine learning models without human expert intervention. In this paper, we introduce the Automated Machine Learning System for Model selection and hyperparameter Optimization (AMLSMO)—a state-of-the-art, all-encompassing AutoML system that combines the power of meta-learning-based warm-starting, Bayesian Optimization with …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 15–23 Read article
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5 Pen PC Technology: A Portable Computer
Abstract: A recent advancement in the field of pen computing is known as “5 pen technology.” Computers have a considerably bigger impact on our lives than most of us may realize. Becoming proficient in computer software has become essential for most occupations. The ENIAC, the first computer ever created in 1943, had more power than several hundred contemporary PCs and was the size of a big room. Integrated circuit-based modern computers …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 2, 2023 · pp. 29–34 Read article
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Optimal Thermal Generating Unit Commitment via Evolutionary Algorithms: A Review
Abstract: This paper presents a literature survey of economic load dispatch problem. The economic load dispatch (ELD) is one of the most important optimization problems of electrical power system. The aim of the ELD problem is to determine the power productions of total generating units from a system in order to have minimum fuel cost, and to meet the all constrains. Solving ELD involves conveying a precise model of optimization and …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 3, Issue 2, 2016 · pp. 26–32 Read article
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Database Intrusion Detection Using Genetic Support Vector Fuzzy Clustering Learning Model
Abstract: AbstractThe rapid development of computer networks and increasing dependency of almost all companies and government agencies on Internet and cloud computing lead to the problem of stability and security like intrusions in several forms which can cause huge loss to these organizations. During recent years, disaster in data due to intrusions has dramatically increased. The hindrance of such intrusions is entirely dependent on their detection part which can be possible …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 2, 2019 · pp. 32–40 Read article
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Design and Implementation of a Four-Port DC to DC Converter for a Hybrid Energy System
Abstract: A four-port DC-DC converter has been developed for integrating a hybrid energy from renewable sources system into an AC microgrid. This converter is particularly suitable for AC microgrid applications that require system-level power management. It boasts a straightforward design, making it effective for interfacing sources with varying voltage and current characteristics. The converter is created to connect a battery bank, a photovoltaic (PV) panel, a wind turbine, and an inverter, …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 2, 2024 · pp. 47–60 Read article
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Feature Extraction and Analysis of Bearing Faults: A Review
Abstract: One of the most important steps in identifying bearing problems is feature extraction. In order to provide a more meaningful dataset, it entails locating and extracting pertinent features from raw bearing vibration signals. Tasks involving categorization and prediction can then make use of these attributes. In many practical applications, such as monitoring rotating machinery or electronic components, the raw signals collected (e.g., vibration, current, temperature) are often complex, high-dimensional, and …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 20–28 Read article
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Harnessing Deep Learning to Explore Microbial Community Structure and Carbon Storage Capacity in Mangrove Ecosystems: A Framework for Computationally
Abstract: Mangrove ecosystems represent one of the most efficient natural carbon sinks on Earth, functioning as critical blue carbon habitats that sustain diverse microbial communities responsible for biogeochemical cycling and long-term carbon storage. Despite their global ecological significance, accurately quantifying and predicting carbon sequestration in mangrove systems remains challenging due to the complex interactions between microbial diversity, sediment chemistry, and environmental drivers. This study presents a comprehensive and sustainable artificial intelligence …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 41–49 Read article
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Cyberattack Detection System in Private Cloud
Abstract: As cloud computing adoption in colleges continues to rise, the security of private cloud systems has become a paramount concern. Data breaches resulting from cyberattacks can inflict severe damage to a university's revenue and reputation. This research proposes a novel machine learning-based cyber threat detection system tailored to the university's private cloud environment. The system's main objective is to continuously monitor the cloud infrastructure and employ advanced machine learning algorithms …
Published in Recent Trends in Parallel Computing · Vol. 10, Issue 2, 2023 · pp. 37–44 Read article
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Automated Microstructure Classification with Class-Specific Segmentation for Titanium Based Composite Materials
Abstract: In engineering, characterisation of microstructure is required to determine and forecast behaviour of titanium alloys. Our proposal in this work has been a deep-learning-based framework in the automatic classification and segmentation of Titanium Based Composite Material. The framework then uses EfficientNetB0 backbone, where we have chosen the backbone to scale the performance of classification and the computational efficiency with the assistance of the transfer learning and the compound scaling. In …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 424–433 Read article