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54 articles for “classification algorithm”
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Machine Learning Approach for Analysis of Ionosphere Parameters for Earthquake Precursors
Abstract: This research explores the relationship between seismic events and predictive indicators, focusing on machine learning-based strategies for early earthquake prediction. It dissects existing prediction approaches, highlighting ionospheric anomalies' correlation with seismic occurrences, particularly preceding earthquakes of magnitudes higher than 5.5. By identifying a lack of comprehensive long-term analyses in the field, the study emphasizes future trends in machine learning-driven EQ-PD techniques using GPS-TEC data for real-time anomaly detection. The methodology …
Published in International Journal of Geological and Geotechnical Engineering · Vol. 9, Issue 2, 2023 · pp. 37–46 Read article
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COVID-19 Detection Using Decision Tree Support Vector Machine Random Forest.
Abstract: The rapidly spreading novel coronavirus (SARS-CoV-2) presents a substantial global health risk, necessitating swift detection through efficient diagnostic methods. Reports highlight lung-related issues in many COVID-19 patients, and both chest CT scans and X-rays are effective in identification. Chest X-ray (CXR) imaging, due to its convenience, faster imaging, simplicity, and lower cost, stands out. In our study, we applied Decision Tree, Random Forest, and Support Vector Machine to identify COVID-19 …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 9, Issue 2, 2023 · pp. 7–21 Read article
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Image Enhancement and Lung Cancer Detection Using Anisotropic Diffusion Filter
Abstract: The leading cause of cancer-related deaths globally is lung cancer. According to the Global Cancer Statistics lung cancer is the leading cause of cancer-related fatalities with 1.8 million deaths and 2.1 million new cases. Early detection of a tiny tumor can stop cancer from spreading and greatly enhance prognosis and survival rates. Consequently, the creation of a sophisticated computer-aided diagnosis system (CADS) may be advantageous for the early therapy of …
Published in International Journal of Analytical and Applied Chemistry · Vol. 9, Issue 1, 2023 · pp. 21–29 Read article
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Semantic Segmentation for Object Detection in Videos using Mask RCNN
Abstract: The segmentation of object instances is an essential step in real-time video detection. Object detection is the problem of detecting the information of all types of items in an image by designating their location with a rectangular box. Using its remarkable feature-learning capabilities, deep learning promotes object detection research. Numerous researchers have utilised various machine learning algorithms for object detection and have focused on enhancing the accuracy of feature extraction. …
Published in International Journal of Digital Communication and Analog Signals · Vol. 8, Issue 2, 2022 · pp. 7–15 Read article
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Recent Advances in Hand Gesture Recognition: A Review of Algorithms and Applications
Abstract: When it comes to human communication, hand movements are crucial in sign language. People who are Deaf or Hard of Hearing communicate with hand gestures. The experimental plan of action makes use of a reasonably priced, solid-position web camera with a 10 mega pixel resolution that is mounted on the computer monitor's outer border. It takes pictures using Red, Green, and Blue [RGB] to enlarge space from a tight distance. …
Published in International Journal of Analog Integrated Circuits · Vol. 9, Issue 2, 2023 · pp. 22–28 Read article
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Performance Comparison of Handwritten Digit Recognition Using Machine Learning Techniques
Abstract: Handwritten pattern, character and digit recognition has always been the most demanding and interesting fields of image processing. The objective of this work is representing and demonstrating the algorithms which are used to recognize handwritten digits. Recognition of handwritten digits has always a bit complex, but it is mostly used in various day-to-day applications. In the task of recognition, the digits are not correctly or accurately scripted or written as …
Published in International Journal of Digital Communication and Analog Signals · Vol. 7, Issue 1, 2021 · pp. 9–18 Read article
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Seed Quality Analysis by Using Image Processing
Abstract: Globally, wheat is the principal source of vegetable protein in human food, having higher protein content than other major cereals like maize and rice. In terms of total production tonnages used for food, India is currently at second rank as the main human food crop. Determining the quality of wheat is critical. Specifying the characteristics of wheat manually needs an expert decision and is time consuming. Sometimes the variety of …
Published in International Journal of Software Computing and Testing · Vol. 3, Issue 1, 2017 · pp. 52–59 Read article
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Wheat Grain Quality Analysis Using Image Processing
Abstract: Rice and Wheat are two major staple cereals used globally. In India too, both of these crops are cultivated and consumed in large quantities. In this article, we are demonstrating an image processing approach to segregate bad quality wheat seed grains from the good quality. Wheat is not only the source of carbohydrate, but it also contains protein in ample amounts. The protein content in wheat is higher than that …
Published in International Journal of Digital Communication and Analog Signals · Vol. 3, Issue 1, 2017 · pp. 35–42 Read article
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Evaluation of Deep Learning Optimizers for Gujarati Handwritten Numerals
Abstract: Handwritten digit recognition is a fundamental task in the field of pattern recognition and computer vision with numerous applications. The development of deep learning algorithms has greatly increased the efficiency and accuracy of recognition of handwritten digits systems. However, the choice of optimizer plays a crucial role in determining the convergence rate and final performance of deep learning models. In this study, we provide a thorough analysis of many deep …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 1, 2025 · pp. 34–41 Read article
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Image Denoising Using IBP n Filter
Abstract: Abstract The ultrasound images are blurred by the multiplicative noise that is the Speckle pattern. It decreases the contrast and resolution of ultrasound images those outcomes in weak interpretation of image characteristics. In several image processing mechanisms like segmentation, classification and pattern recognition the speckle is a significant part. The conventional methods calculate the computation of LBP on gradient. The limitation of this technique was that the LBP mechanism divide …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 4, Issue 2, 2018 · pp. 37–45 Read article
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Employing ML and DL to Optimize an ElectrochemicalBiosensor
Abstract: A major field of study in science, that have made the understanding of the world and made homo sapiensthe dominant species on the planet is our understanding of medicine. Under this vast umbrella is thedetection and classification of microorganisms. Electrochemical biosensors have emerged aspromising tools in this regard due to their high sensitivity, selectivity, and potential for miniaturization.By integrating a Machine Learning & Deep Learning model for the detection of …
Published in International Journal of Chemical Separation Technology · Vol. 10, Issue 1, 2024 · pp. 33–38 Read article
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Hybrid Quantum-Classical Signal Processing for High-Dimensional Feature Extraction in Smart Instrumentation
Abstract: Hybrid quantum–classical signal processing has emerged as a promising paradigm for overcoming the computational limitations of conventional algorithms in analyzing high-dimensional data generated by modern smart instrumentation systems. This paper presents a novel hybrid quantum–classical signal processing framework designed for efficient feature extraction from complex, multidimensional sensor signals encountered in industrial monitoring, biomedical diagnostics, environmental sensing, and intelligent manufacturing. The proposed architecture integrates quantum variational circuits with classical deep learning …
Published in International Journal of Microwave Engineering and Technology · Vol. 12, Issue 2, 2026 Read article
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Hybrid Quantum-Classical Signal Processing for High-Dimensional Feature Extraction in Smart Instrumentation
Abstract: Hybrid quantum–classical signal processing has emerged as a promising paradigm for overcoming the computational limitations of conventional algorithms in analyzing high-dimensional data generated by modern smart instrumentation systems. This paper presents a novel hybrid quantum–classical signal processing framework designed for efficient feature extraction from complex, multidimensional sensor signals encountered in industrial monitoring, biomedical diagnostics, environmental sensing, and intelligent manufacturing. The proposed architecture integrates quantum variational circuits with classical deep learning …
Published in International Journal of Microwave Engineering and Technology · Vol. 12, Issue 2, 2026 Read article
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Network Intrusion Detection Using Wireshark and Machine Learning
Abstract: The growth of networked devices has highlighted the desire for advanced intrusion detection (IDS) tools to protect digital systems from evolving cyber threats. Traditional IDS systems are often difficult to adapt to the threat environment because they rely on predefined signature lists. This study presents a new approach that combines Wireshark, a widely used network packet analysis tool, with advanced machine learning for intrusion detection. Our system leverages Wireshark's data …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 10, Issue 1, 2024 · pp. 23–31 Read article