Titlebook: Computation of Artificial Intelligence and Machine Learning; First International Amit Kumar Bairwa,Varun Tiwari,Thittaporn Ganokrat Confer

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Konrad Fleischer,Hans Heinz Naumann year and more and limit the daily activities of patients. They need continues monitoring. According to WHO most affected people are from low and middle-income countries. People with low educational background and poor life styles are mostly affected with chronic diseases. These diseases are causing

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Konrad Fleischer,Hans Heinz Naumannagnosis thanks to computer-aided solutions. The current research study demonstrates that computer-assisted diagnostics makes extensive use of deep learning technologies especially using transfer learning approaches. These techniques make extensive use of baseline models like VGG16, Inception, ResNet

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Konrad Fleischer,Hans Heinz Naumannribution companies, as well?as society as a whole. In a comprehensive survey targeting educated individuals, the findings of a societal cost-benefit analysis revealed several positive outcomes. These included energy savings for consumers, decreased market costs due to enhanced transparency, and redu

Dignant

Konrad Fleischer,Hans Heinz Naumannibute to the increase in undistributed energy. In Benin, the most recurring disturbances recorded on the High Voltage category A (HTA) distribution networks of the Beninese Electric Energy Company (SBEE) are fugitive faults, homopolar faults and blackouts. Despite the positioning of the recloser cir

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https://doi.org/10.1007/978-3-658-42747-4ithin social media platforms. By utilizing cutting-edge techniques, the framework performs exceptionally well in examining current ties as well as predicting future connections, which adds to a more sophisticated comprehension of the complex web of connections seen in social networks. Central to its

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Akademisches Controlling an Hochschulenthis state, a series of angles is often measured manually, with the quality of the measurement greatly relying on the experience of the individual taking it. There have been many attempts to predict the weight-bearing line (WBL) ratio using simple knee radiographs. This paper suggests a convolutiona

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Validierung analytischer Verfahren,ts limited resources. For this, we manually tagged a corpus of 50,000 POS-tagged sentences and trained it using a Hidden Markov Model (HMM). Since no prior work had been reported in this area, we couldn‘t compare our results to any other system. This paper documents the efforts made to create an HMM

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