One of the most important aspects of civilization is human wellness. The best and most accurate condition analysis seeks to offer the necessary assistance as soon as practical. The clinical research factor necessitate...
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Blockchain is a disruptive technology that changed how financial operations and ownership exist over the internet. With the implementation of smart contracts in blockchains, facilitation of transactions without interm...
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In this ambitious agricultural project, cutting-edge technologies such as Machine Learning (ML) and Deep Learning (DL) are harnessed to revolutionize farming practices in India. The primary focus lies in automating vi...
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Handwritten Digit Recognition (HDR) refers to the computer' s ability to identify and categorize hand written digits from various sources into 10 predetermined categories, ranging from 0 to 9. The issue of digit r...
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One of the biggest challenges in machine vision is finding and identifying items in natural scenes. When real-time processing capabilities are needed, this difficulty is exacerbated. Intelligent transport systems rely...
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In the field of facial identity authentication, silent face anti-spoofing detection, as a key technology, to prevent fake photos and videos, is receiving widespread attention. To address the issue of low detection acc...
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Internet of Things (IoT), in a blend with advanced computer vision techniques, models new challenges for end users in securing images and videos. Securing images becomes one of the crucial aspects in the enormous and ...
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Image segmentation is an important problem in the field of image processing. Traditional multi-threshold image segmentation faces the problems of inefficiency and lack of real-time performance. In order to improve the...
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Millions of people have died as a result of uncontrollably rising blood sugar levels throughout the world. This can be a result of a delayed diabetes diagnosis. A lack of a cohesive framework, data imbalance, and inad...
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Machine Learning(ML)has changed clinical diagnostic procedures *** in Cardiovascular Diseases(CVD),the use of ML is indispensable to reducing human *** studies focused on disease prediction but depending on multiple p...
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Machine Learning(ML)has changed clinical diagnostic procedures *** in Cardiovascular Diseases(CVD),the use of ML is indispensable to reducing human *** studies focused on disease prediction but depending on multiple parameters,further investigations are required to upgrade the clinical ***-layered implementation of ML also called Deep Learning(DL)has unfolded new horizons in the field of clinical *** formulates reliable accuracy with big datasets but the reverse is the case with small *** paper proposed a novel method that deals with the issue of less data *** by the regression analysis,the proposed method classifies the data by going through three different *** the first stage,feature representation is converted into probabilities using multiple regression techniques,the second stage grasps the probability conclusions from the previous stage and the third stage fabricates the final *** experiments were carried out on the Cleveland heart disease *** results show significant improvement in classification *** is evident from the comparative results of the paper that the prevailing statistical ML methods are no more stagnant disease prediction techniques in demand in the future.
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