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24 articles for “SVM”
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An Evaluation of CNN and SVM Algorithms for Facial Recognition
Abstract: With the use of facial recognition technology, someone's identity can be confirmed or identified. Real-time or picture-based facial recognition technology can be used to identify individuals. One of the most important elements in the field of biometric security is facial recognition. The technology is mostly used in the fields of law enforcement and defence, while interest in other fields is growing. To recognize the face, numerous technologies and algorithms were …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 1, Issue 2, 2023 · pp. 12–19 Read article
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Malicious Application Detection in Windows Using SVM Algorithm
Abstract: In recent years, both the development of Windows application clients and the uses of smart mobile phones have increased significantly. As the number of Windows application users continues to grow, there is a rise in malicious individuals who develop harmful Windows applications with the intent of unlawfully obtaining confidential information and engaging in fraudulent activities. These applications are designed to target vulnerable areas such as mobile banking and digital wallets, …
Published in International Journal of Mobile Computing Technology · Vol. 1, Issue 1, 2023 · pp. 30–36 Read article
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Machine Learning Approaches Towards Resume Classification
Abstract: Finding the right person for an open position can be an unnerving task, especially when there are many applicants, and if the recruiter or the Human Resources department must sort and further categorize all those resumes then it will be a labor-intensive, time-consuming, and tiresome task. Additionally, human assessment of resumes may be biased and prone to mistakes. Manually screening the proper candidate's resume from the pool is not practicable; …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 1–7 Read article
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AI-Based Criminal Identification System A Breakthrough Approach
Abstract: Identifying and locating a perpetrator is a time-consuming and difficult process. The perpetrators are growing more skilled, leaving no biological evidence or fingerprint impressions at the crime scene. Using cutting-edge face recognition technology is a quick and easy solution. Through the use of linear programming, this research presents an innovative approach to classifying all face tracks collectively. In addition to the following, it incorporates: a novel method for extracting more …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 1, 2024 · pp. 1–14 Read article
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article
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Machine Learning Based Sentiment Analysis of Student Feedback in Higher Education
Abstract: Educational institutions routinely collect feedback from students to understand their perceptions of academic programs, infrastructure, and campus facilities, to improve the overall quality of the college environment. In current practice, feedback is often gathered using numerical or grade-based rating systems, which tend to oversimplify student opinions and may overlook important details related to their level of satisfaction. In contrast, open-ended textual feedback allows students to clearly express their views, concerns, …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 01–10 Read article
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Matching Minutiae Fingerprint Q-Learning Approach for Detail Coordination: Identifiable Mark Point
Abstract: The use of fingerprints for high-precision recognition and identification of people is one of the most reliable biometric symbols because it is non-invasive. In this paper, we propose an innovative approach to detect details on low contrast resolution image quality of fingerprint images. Existing algorithms are not very susceptible to sound and image excellence due to the lack of level of intensity. We recommend a reliable route to find fingerprints …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 1, 2023 · pp. 1–15 Read article
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Heart Attack Prediction Using Machine Learning
Abstract: Heart attacks have become a prevalent and serious condition in recent years due to a variety of causes. Numerous variables, including age, sex, fat, and others, can be used to predict it. In the current study, it was found that a data set with 13 parameters and 302 distinct data values, collected from a Kaggle dataset to assess patient condition, was covered. This article delves into the application of machine …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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Machine Learning Based Early Cataract Detection: A Predictive Modeling Approach
Abstract: Cataracts, characterized by dense cloudy areas in the eye’s lens, afflict more than 50% of elderly individuals, leading to impaired vision and potential blindness. Detecting cataracts at an early stage is crucial to facilitate simpler treatments, as neglecting the condition may necessitate complex eye surgery. To address this issue, we are creating a predictive system that identifies cataract disease by analyzing user-provided eye features. To achieve this, we leverage OpenCV, …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
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Methods Based on Machine Learning for Large-scale Classification of Crop Leaf Diseases
Abstract: Worldwide productivity of crops is seriously threatened by crop leaf diseases, which can result in large crop losses and negative economic effects. Effective disease management and crop protection depend on the early and precise detection and classification of these illnesses. Machine learning approaches have gained popularity recently due to their ability to automate procedures related to illness diagnosis and classification. An overview of the several machine learning–based methods used for …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 11–23 Read article
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Using Machine Learning for Key phrase Extraction in Digital Libraries
Abstract: Machine learning has revolutionized various aspects of information retrieval, including key phrase extraction in digital libraries. Key phrase extraction is crucial for summarizing and categorizing vast amounts of textual data, enabling efficient search and retrieval processes. This study explores the application of machine learning techniques for automatic key phrase extraction in digital libraries. We review various supervised and unsupervised learning algorithms, including deep learning models, that are employed to identify …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 8–13 Read article
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Diabetes Risk Prediction from Survey Data Using Machine Learning Algorithms
Abstract: Diabetes mellitus represents one of the most significant global health challenges, affecting millions worldwide and leading to severe complications if left undiagnosed or poorly managed. Early detection and risk assessment are crucial for preventing the progression of this chronic condition. This research presents a comprehensive machine learning approach for predicting diabetes risk using survey-based health parameters. The study implements and compares four prominent classification algorithms: Logistic Regression, K-Nearest Neighbors (KNN), …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Baggage Detection and Recognition Using Local Tri-Directional Pattern
Abstract: Nowadays, pattern-based image retrieval algorithms are gaining popularity just because of their uniqueness. There are several issues in the previously proposed systems. The proposed system resolves issues highlighted in the literature. Our proposed system is tested on two image datasets ILIDS and PETS 2006. LTDP provides good results as compared to LBP in baggage detection on two classes that either bag is present or not in an image because LTDP …
Published in International Journal of Mobile Computing Technology · Vol. 1, Issue 1, 2023 · pp. 8–17 Read article
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Implementation of Anticipating Rainfall Using Machine Learning
Abstract: Rainfall forecasting is crucial for many aspects of our national economy and should help prevent major seasonal droughts. Since agriculture is a beloved profession in many states, some Asian countries are economically hooked to decline. Previous precipitation info is beneficial. Farmers are cancerous in managing their crops, resulting in economic progress for the country. downfall prediction is hard for earth science scientists because of unordering time and unordered quantity of …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 1, 2023 · pp. 1–8 Read article
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Classification and Detection of Brain Tumor using Convolutional Neural Network
Abstract: Tumors are masses created when brain cells multiply uncontrollably. A brain tumor is the medical term for this condition. Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Developing a treatment plan is essential to raising a patient's standard of living. Tumors in different regions of the body are evaluated using a variety of imaging techniques, with MRI pictures being utilized mostly for …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 8–13 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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Comparative Analysis of Heart Disease Prediction System
Abstract: In the present world, where heart illnesses are on the rise, it is crucial to forecast these diseases. Performing the task on heart disease is a bit difficult and it must be finished precisely and successfully. Heart disease identification relies heavily on Machine Learning (ML) and data mining approaches. The primary focus of the review paper is that patients are easily prone to cardiac diseases depending on medical traits. Using …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 1, 2023 · pp. 1–6 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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Eye Disease Classification Using K-means Clustering Algorithm and Ensemble Classification Approach
Abstract: In this study, we present a comprehensive approach for the classification of eye diseases, specifically targeting normal, cataract, glaucoma, and diabetic retinopathy conditions. This research uses a dataset from Kaggle, which provides a wide and varied collection of retinal images to ensure good representation. The methodology encompasses advanced image processing and machine learning techniques to ensure accurate diagnosis and prediction. The preprocessing phase involves a series of image enhancement techniques …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 15–27 Read article
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article