School bus contributes positively to reducing the number of cars on the road, thereby reducing the environmental impact of cars. It also dramatically relieves working parents, who do not have to pick up and drop off t...
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Machine Learning(ML)-based prediction and classification systems employ data and learning algorithms to forecast target ***,improving predictive accuracy is a crucial step for informed *** the healthcare domain,data a...
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Machine Learning(ML)-based prediction and classification systems employ data and learning algorithms to forecast target ***,improving predictive accuracy is a crucial step for informed *** the healthcare domain,data are available in the form of genetic profiles and clinical characteristics to build prediction models for complex tasks like cancer detection or *** ML algorithms,Artificial Neural Networks(ANNs)are considered the most suitable framework for many classification *** network weights and the activation functions are the two crucial elements in the learning process of an *** weights affect the prediction ability and the convergence efficiency of the *** traditional settings,ANNs assign random weights to the *** research aims to develop a learning system for reliable cancer prediction by initializing more realistic weights computed using a supervised setting instead of random *** proposed learning system uses hybrid and traditional machine learning techniques such as Support Vector Machine(SVM),Linear Discriminant Analysis(LDA),Random Forest(RF),k-Nearest Neighbour(kNN),and ANN to achieve better accuracy in colon and breast cancer *** system computes the confusion matrix-based metrics for traditional and proposed *** proposed framework attains the highest accuracy of 89.24 percent using the colon cancer dataset and 72.20 percent using the breast cancer dataset,which outperforms the other *** results show that the proposed learning system has higher predictive accuracies than conventional classifiers for each dataset,overcoming previous research ***,the proposed framework is of use to predict and classify cancer patients ***,this will facilitate the effective management of cancer patients.
The Internet, as the world's largest computer network, has evolved beyond a mere repository of information to become an indispensable tool driving modern society. Its dynamic nature enables communication, interact...
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Depth cameras used in visual feedback loops typically produce point clouds or their voxelized images. In the paper, we introduce an original sparse convolutional neural network structure tailored to work with 3D point...
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Mycobacterium tuberculosis, the causal agent of tuberculosis, is a major global health concern. The most widely studied strain for understanding the mechanism of drug resistance is H37Rv. To identify possible therapeu...
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Health misinformation on social networking sites (SNS) is a critical issue, particularly during health crises like the COVID-19 pandemic. The spread of inaccurate health information can lead to severe outcomes, includ...
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作者：
PrathyakshiniPrathwiniPratheeksha Hegde, N.VaishaliRashmi, N.Kumar, Archana Praveen
NMAM Institute of Technology Department of Information Science and Engineering Karkala Nitte India
NMAM Institute of Technology Department of Master of Computer Applications Karkala Nitte India
NMAM Institute of Technology Department of Computer Science and Engineering Karkala Nitte India Manipal Academy of Education
Manipal Institute of Technology Department of Computer Science and Engineering India
Speech recognition systems play an integral role in numerous applications, from virtual assistants to accessibility tools. This paper offers a new viewpoint to speech recognition utilizing computer vision and deep lea...
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In standard iris recognition systems,a cooperative imaging framework is employed that includes a light source with a near-infrared wavelength to reveal iris texture,look-and-stare constraints,and a close distance requ...
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In standard iris recognition systems,a cooperative imaging framework is employed that includes a light source with a near-infrared wavelength to reveal iris texture,look-and-stare constraints,and a close distance requirement to the capture *** these conditions are relaxed,the system’s performance significantly deteriorates due to segmentation and feature extraction ***,a novel segmentation algorithm is proposed to correctly detect the pupil and limbus boundaries of iris images captured in unconstrained ***,the algorithm scans the whole iris image in the Hue Saturation Value(HSV)color space for local maxima to detect the sclera *** image quality is then assessed by computing global features in red,green and blue(RGB)space,as noisy images have heterogeneous *** iris images are accordingly classified into seven categories based on their global RGB *** the classification process,the images are filtered,and adaptive thresholding is applied to enhance the global contrast and detect the outer iris ***,to characterize the pupil area,the algorithm scans the cropped outer ring region for local minima values to identify the darkest area in the iris *** experimental results show that our method outperforms existing segmentation techniques using the UBIRIS.v1 and v2 databases and achieved a segmentation accuracy of 99.32 on UBIRIS.v1 and an error rate of 1.59 on UBIRIS.v2.
The heart plays a pivotal role in the functioning of living organisms, making its diagnosis and prediction of related diseases a matter of utmost importance. Approximately 17.9 million individuals succumb to cardiovas...
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Current drug recommendation systems primarily rely on data-driven approaches, which often overlook the importance of incorporating prior knowledge and capturing temporal dependencies in patient histories. To address t...
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