Search
14 articles for “Nearest neighbor (NN)”
-
A Study on K-Nearest Neighbor Techniques with Other Techniques
Abstract: AbstractThe closest neighbor (NN) system is basic, exceptionally proficient and feasible in the field of example acknowledgment, content arrangement, object acknowledgment and so forth. Its straightforwardness is its primary preferred position; however, the impediments cannot be overlooked even. The memory necessity and calculation unpredictability are moreover matters. Numerous methods are created to defeat these restrictions. NN procedures are comprehensively ordered into structure less and structure-based procedures. In this paper, we …
Published in Journal of Open Source Developments · Vol. 7, Issue 3, 2020 · pp. 7–11 Read article
-
Automatic Baby Cry Detector with sleep music player (ABCD)
Abstract: In today’s world, our lives have become moredependent on technology. One problem which caught our eyesis when parents have to leave their wards (aged between 3months to 2 years) alone due to some essential tasks for a shortduration, the baby goes unmonitored. Normally, parents dothis by leaving their child asleep. In many cases, the childwakes up and starts to cry. In absence of loved ones, babiesneed immediate calmness relief. A …
Published in Journal of Mechatronics and Automation · Vol. 10, Issue 1, 2023 · pp. 21–29 Read article
-
A New Systematic Approach of Using SVM, KNN, PNN and CNN to Achieve Higher Accuracy for Classification and Recognition of Music Genre
Abstract: In order to overcome challenges like finding songs that are similar, figuring out which cultures would enjoy particular music, conducting surveys, and using music as therapy, classification and recognition of music genres are essential. The expansion of music-related content available online has created new opportunities for the development of music referral systems, which support user communities in searching, finding, sharing, and producing digitally. Our aim is to develop a systematic …
Published in Journal of Operating Systems Development & Trends · Vol. 10, Issue 1, 2023 · pp. 1–11 Read article
-
Development of Fast and Power Efficient Elevator
Abstract: The rapid urbanization and vertical expansion of cities have led to a surge in the construction of high-rise buildings, creating a growing demand for elevator systems that are not only fast but also energy efficient. As population density in metropolitan areas increases, the pressure on vertical transportation systems intensifies, highlighting the need for solutions that can handle high passenger traffic without compromising performance or sustainability. This study presents the development …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 32–41 Read article
-
Fault Investigation of Rolling Element Bearing using Soft Computing
Abstract: AbstractRolling element bearing is the most significant mechanical component of any rotating machinery and used in vast applications from the surgical machine tool to aircraft etc. In the present research, an experimental investigation has been done using vibration analysis, continuous wavelet transform (CWT), and soft computing, i.e., support vector machine (SVM) and k-nearest neighbor (k-NN) for fault detection and diagnosis of rolling element bearing. Vibration signatures in the time domain …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 1, 2019 · pp. 8–22 Read article
-
Advancing Healthcare Systems: A Machine Learning Approach to Multi-Disease Prediction
Abstract: The integration of machine learning algorithms in healthcare has revolutionized the way we approach disease prediction and diagnosis. An attempt to employ machine learning techniques to forecast numerous diseases is presented in this study. A diverse dataset containing patient records, medical history, and relevant features for various diseases was used to develop predictive models. Feature selection and normalization were among the preprocessing methods used to clean and prepare the data. …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 1, 2025 · pp. 1–6 Read article
-
Multiple Disease Prediction Using Machine Learning Algorithms
Abstract: The incorporation of machine learning algorithms into healthcare has transformed disease prediction and diagnosis. This research introduces a method for predicting various diseases using machine learning techniques. A comprehensive dataset, consisting of patient records, medical histories, and key disease-related features, was utilized to build predictive models. Data preprocessing methods, including feature selection and normalization, were implemented to clean and prepare the dataset. Several machine learning algorithms, such as Decision Trees, …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 3, 2024 · pp. 34–38 Read article
-
Alzheimer’s Disease Detection Using ML Algorithm
Abstract: A degenerative neurological state of affairs, Alzheimer's disease (AD) gradually impairs cognitive and functional capacities, especially in people over 65. Early AD detection is crucial for efficient management and treatment prep. This study delves into novel approaches for the early detection of AD using non-invasive methods. We've implemented a blend of neuroimaging data analysis and machine learning algorithms to pinpoint markers indicative of the disease during its initial phases. Our …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 3, 2024 · pp. 53–57 Read article
-
Deep Learning Based Detection and Classification of Brain Tumors Using MRI Images
Abstract: Brain tumor detection using magnetic resonance imaging (MRI) is a critical task in the early detection and treatment of brain tumors. Manual analysis of brain tumor detection using MRI is a tedious task that requires expertise in the field. Therefore, this study proposes a deep learning-based approach for brain tumor detection and classification using Convolutional Neural Networks (CNN). The proposed approach preprocesses the MRI image using normalization, resizing, and noise …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
-
Machine Learning Techniques Utilised for Autism Spectrum Disorder Detection
Abstract: A neurological developmental illness called autism spectrum disorder impacts a person’s ability to connect, communicate, and learn. Autism spectrum disorder influences individuals in distinct ways, as do the severity and its manifestations. Often, this illness is diagnosed in individuals between the ages of 1 and 5 years, and the symptoms include unique behaviours, interests, and potential social difficulties. In order tTo lessen the rise in instances of autism, it must …
Published in Journal of Control & Instrumentation · Vol. 14, Issue 1, 2023 · pp. 32–37 Read article
-
A Novel Feature Level Fusion Method for Classification of Remote Sensing Images
Abstract: Feature level fusion approach is utilized in this paper to classify remote sensing images. Texture features are extracted from panchromatic images using mixed Gabor filter (GB), fast gray level co-occurrence matrix (GLCM) and linear binary pattern (LBP). The resultant texture features are classified using nearest neighbor (k-NN) classification method. Spectral features are extracted from the MS image and segmented using over segmented k-means algorithm with novel initialization (OSKNI). Finally the …
Published in Journal of Remote Sensing & GIS · Vol. 10, Issue 1, 2019 · pp. 58–65 Read article
-
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
-
Reducing the Dimensional Dependence for Rank-based Similarity Search
Abstract: In this paper, we try to introduce a data structure for k-NN search, the Rank Cover Tree (RCT). The pruning tests for RCT rely on the comparison of similarity values not on the other properties of the underlying space, such as the triangle inequality. Objects are selected according to their ranks with respect to the query object, allowing much tighter control on the overall execution costs. Theoretical analysis shows that …
Published in Journal of Advanced Database Management & Systems · Vol. 2, Issue 3, 2015 · pp. 20–25 Read article
-
Reducing the Dimensional Dependence for Rank-Based Similarity Search
Abstract: In this paper a data structure for k-NN search, the rank cover tree (RCT) is implemented. The pruning tests for RCT rely on the comparison of similarity values and not on the other properties of the underlying space, such as the triangle inequality. Objects are selected according to their ranks with respect to the query object, allowing much tighter control on the overall execution costs. Theoretical analysis shows that with …
Published in Journal of Advanced Database Management & Systems · Vol. 3, Issue 1, 2016 · pp. 9–17 Read article