Zarin Tasnim

TL;DR: This paper uses MobileNet, a state of art (convolutional neural network) CNN architecture which is designed for mobile devices as it requires less computing power, for handwritten character recognition and achieves 96.46% accuracy in recognizing 231 classes.

TL;DR: In this article , a survey was conducted to estimate the prevalence and predictive factors of vaccine hesitancy among parents of children with neurodevelopmental disorders (NDD), and the authors found that parents who were either not vaccinated or did not receive the COVID-19 vaccine themselves (AOR = 12.14, 95% CI = 8.48-17.61; p = 0.040).

TL;DR: A model and computer system is proposed that can recognize Bangla Sign Lanugage alphabets and translate them to corresponding Bangla letters by means of deep convolutional neural network (CNN).

TL;DR: A detailed overview of different existing methods/systems of fall detection based on contactless sensors can be found in this paper, where the authors define existing approaches for potential research directions and analyze the elderly fall detection system's ongoing practices.

TL;DR: In this article, four different machine learning algorithms (SVM, KNN, Naive Bayes, Random Forest and Random Forest) were implemented to show how their performance varies on different datasets having different set of attributes or features by keeping the same number of data instances, for predicting breast cancer and it's recurrence.