Titlebook: Applied Computational Technologies; Proceedings of ICCET Brijesh Iyer,Tom Crick,Sheng-Lung Peng Conference proceedings 2022 The Editor(s) (

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Detection of Disease in Plants with Android Integration Using Machine Learning the agriculture field due to the non-availability of required infrastructure. They are usually caused by pests, insects, bacteria and significantly reduce productivity if not controlled on time. Farmers face losses due to various plant diseases. It is difficult for farmers to monitor and identify c

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Analysis of Post-flood Impacts on Sentinel-2 Data Using Non-parametric Machine Learning Classifiers:quality multispectral satellite data. Flood mapping is an important activity for mapping the changes over the given study region for disaster preparedness and carrying out post-disaster mitigation plans. The study’s main objective is to map the waterlogged and silt-affected areas. In this study, thr

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机构

Performance Analysis of Cardiovascular Diseases Using Machine Learningere and leading cause of death. Various factors like Age, Blood Pressure, Stressful life, and work culture have shown the impact on increasing the cases of CVD causing many deaths, and hence its early detection is of paramount importance. Smart healthcare for preventive measures is becoming a popula

Fibroid

A Deep Learning Paradigm for Computer Aided Diagnosis of Emphysema from Lung HRCT Imagesstage of COPD and proliferation of the emphysematous lesions, it is necessary to distinguish between emphysematous and healthy lung tissues. This study discusses a novel approach to determining the lungs’ emphysema through chest C.T. image analysis. For this, an intensity threshold of −910 HU is tak

Folklore

Zamzam A. Elsharif,Bashir M. Galluslearning technique which consists of Error Level Analysis (ELA). ELA produces brighter regions for fake images to differentiate fake and bona fide images. In module3, Artificial Neural Networks (ANN) is used for building the model efficiently. The proposed approach helps detect the bona fide satelli

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https://doi.org/10.1007/978-3-030-39062-4classifier based on poetry elements. Adaboost (AB), Bagging (BG), Bi-directional Long Short Term Memory (Bi-LSTM), C4.5, Gradient Boosting (GB), Hyperpipes (HP), K-nearest neighbor (KNN), Long Short Term Memory (LSTM), Naïve Bayes (NB), PART, Random Forest (RF), Support Vector Machine (SVM), Voting

疏忽

Front Impact Simulation of Urban Bus,ng the input dataset multiple times. The modifications proposed in the model are eviction of the expansion parameter, calculation of centre points and radii of .s in an optimized way, membership functions for various kinds of hyperspheres, and online capability for adaptation of new input patterns o