Titlebook: Machine Intelligence and Emerging Technologies; First International Md. Shahriare Satu,Mohammad Ali Moni,Mohammad Sham Conference proceedi

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書(shū)目名稱Machine Intelligence and Emerging Technologies影響因子(影響力)




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書(shū)目名稱Machine Intelligence and Emerging Technologies讀者反饋




書(shū)目名稱Machine Intelligence and Emerging Technologies讀者反饋學(xué)科排名

Fluctuate

熱心助人

978-3-031-34621-7ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2023

inflate

Isometric

Conference proceedings 2023ies, MIET 2022, hosted by Noakhali Science and Technology University, Noakhali, Bangladesh, during September 23–25, 2022.?.The 104 papers presented in the proceedings were carefully reviewed and selected from 272 submissions. This book focuses on theoretical, practical, state-of-art applications, an

憤憤不平

Design and Implementation of a Drowsiness Detection System Up to Extended Head Angle Using FaceMesh detect the drowsiness of the driver with 97.5% accuracy in straight face position, as well as the response time of the system is calculated that is around 3 s. We have found out that our proposed system is less complex in design, low cost and performs better than related contemporary works.

柔美流暢

Integrated Music Recommendation System Using Collaborative and?Content Based Filtering, and?Sentimen to create a novel dataset and use it to suggest songs based on the mood. K performs better for a smaller value of K, but CF improves as K increases. CF improves as K is increased while K works better for a lower value of K. By comparing all results, TF-IDF outperforms SVM and NB in sentiment analysis.

歸功于

1867-8211 Technologies, MIET 2022, hosted by Noakhali Science and Technology University, Noakhali, Bangladesh, during September 23–25, 2022.?.The 104 papers presented in the proceedings were carefully reviewed and selected from 272 submissions. This book focuses on theoretical, practical, state-of-art applic

hauteur

尊敬

Epileptic Seizure Prediction Using Bandpass Filtering and?Convolutional Neural Networkuracy of 89.5%, sensitivity 89.7%, precision 89.0% and AUC, the area under the curve is 89.5% with our proposed model. In addition, we have addressed several researchers’ seizure prediction models, sketched their core mechanism, predictive effectiveness, and compared them with ours.