M
Meysam Vakili
Researcher at University of Science and Culture
Publications - 4
Citations - 42
Meysam Vakili is an academic researcher from University of Science and Culture. The author has contributed to research in topics: Deep learning & Activity recognition. The author has an hindex of 3, co-authored 4 publications receiving 20 citations.
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Performance Analysis and Comparison of Machine and Deep Learning Algorithms for IoT Data Classification.
TL;DR: Eleven popular machine and deep learning algorithms for classification task using six IoT-related datasets are compared according to several performance evaluation metrics including precision, recall, f1-score, accuracy, execution time, ROC-AUC score and confusion matrix and indicated that Random Forests performed better than other machine learning models.
Journal ArticleDOI
Cloud service selection using cloud service brokers: approaches and challenges
TL;DR: This paper reviews the recent approaches that have been introduced and used for cloud service brokerage and proposes a set of attributes for a CSB to be considered effective, which have wider application in cloud computing environments.
Journal ArticleDOI
Load balancing in MapReduce on homogeneous and heterogeneous clusters: an in-depth review
TL;DR: This paper examines the effectiveness of two main key factors: data locality and data skew on homogeneous and heterogeneous clusters in Hadoop MapReduce.
Posted Content
Incremental Learning Techniques for Online Human Activity Recognition.
Meysam Vakili,Masoumeh Rezaei +1 more
TL;DR: In this paper, the authors proposed a human activity recognition (HAR) approach for the online prediction of physical movements, benefiting from the capabilities of incremental learning algorithms for real-time detection of physical activities.