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9 articles for “K-Nearest Neighbour Classifier”
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K-NN Classification and Thresholding by Fuzzy If-Then Rules using Texture and Shape Feature
Abstract: In present scenario image retrieval is the basic requirement, because of different types of images features are added in database from different sources are available for image retrieval. In Content Based Image Retrieval ‘content based’ means that the search will analyze the actual contents of the image. In this paper texture and shape features are extracted and classifications of images are done with K-Nearest Neighbour. The Fuzzy concept If-Then rules …
Published in Journal of Advances in Shell Programming · Vol. 2, Issue 2, 2015 · pp. 1–11 Read article
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Voting Classification Method for Network Traffic Prediction
Abstract: Prediction analysis (PA) is a data mining-based technique. The futuristic outcomes based on present data can be predicted using this technique. As the dataset is large and complex, network traffic classification is a big concern in prediction analysis. Three phases are included in network traffic strategies. The data collection is obtained in the first step of pre-processing, and it is analysed to delete incomplete and obsolete values. The relationship between …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 1, 2021 · pp. 23–30 Read article
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Facial Biometrics for Attendance System
Abstract: This paper discusses the necessity for effective student attendance management systems by proposing a smart attendance management system utilizing biometric technology. It is well recognised that manually recording attendance is time-consuming and error prone. In this study, we propose a Facial Biometrics attendance system that automates attendance process without requiring human intervention. The system consists of a camera placed in the classroom to take pictures of the pupils. Subsequently, the …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 1, 2024 · pp. 36–44 Read article
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Colour Based Segmentation of a Landsat Image Using K-Means Clustering Algorithm
Abstract: AbstractImage segmentation is one of the typical vintage subjects in image processing and it acts as a bulls-eye of the image processing technique. By definition, image segmentation means identifying the similar regions in the image; or in other words, identifying the homogenous pixels in the image and grouping all these pixels based on the homogeneity condition considered. This homogeneity condition can be like, colour, texture, size, compactness etc. It is …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 4, Issue 3, 2017 · pp. 31–38 Read article
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Data-Driven Machine Learning Approach for Vehicle Fuel Economy Prediction and Performance Monitoring Using Real-World OBD Data
Abstract: Modern passenger vehicles generate large volumes of operational data through On-Board Diagnostics (OBD) systems, enabling continuous observation of vehicle performance under real-world driving conditions. However, much of the existing research mainly analyses previously recorded data and does not provide predictive mechanisms for monitoring vehicle performance under dynamically varying operating conditions. This study presents an AI and machine learning–based method for predicting and monitoring real-world vehicle performance and fuel economy using …
Published in Trends in Machine design · Vol. 13, Issue 2, 2026 · pp. 47–66 Read article
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Effect of Rank Based Correlation on K-Nearest Neighbour
Abstract: AbstractBecause of its simplicity, higher efficiency and effectiveness, K-nearest neighbour (KNN) isthe most popular and chosen algorithm in the last few years. It has many conveniences withthe exception of some inconvenience. In this study, we explore the correlation and dependencebetween attributes, and try to significantly improve the classification accuracy from existingalgorithm by skipping correlated attributes. To get classification accuracy, we applied thisskipping correlated attributes method in KNN ranking based classifier. …
Published in Current Trends in Information Technology · Vol. 7, Issue 2, 2017 · pp. 17–22 Read article
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Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article
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Historical Kannada Handwritten Character Recognition using K-Nearest Neighbour Technique
Abstract: AbstractMost of the historical Kannada handwritten documents are preserved in the manuscript preservation center and archaeological department, and these documents are generally degraded in nature and it is very difficult to read and understand the contents in it. Hence, it is very much essential to digitize the historical Kannada handwritten document and recognize its originality of dynasty. The main objective of this paper is to digitize and recognize the historical …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 1, 2019 · pp. 23–29 Read article
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Local Binary Pattern-based Noise Robust Feature for Texture Classification
Abstract: Abstract: The presence of noise degrades the local binary pattern-based classification efficiency. In the present work, a modified local binary pattern ( —modified noise robust local binary pattern) based classification is proposed. In this, a local binary pattern-based feature is modified, which also captures macrostructure information, whereas the existing features capture microstructure texture information only. The new feature is tested on Outex_TC_00010, Outex_TC_00012 and Brodatz datasets for rotation invariant and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 6, Issue 3, 2019 · pp. 31–47 Read article