… Having too much glucose in your blood can create health problems, and it will be harmful
day by day. More than 25 papers ofML/DL techniques in diabetes detection are analyzed here. …

… Application of ML methods on big data generated in the smart grid to extract useful information
and to detect and protect the data … , Machine learning based network vulnerability analysis …

… and turning them into valuable information is a major challenge in EO domain. This study …
Moreover, a machine learning-based approach is integrated into the cube to enhance parallel …

… Combine the process of visual data encoding and analysis into one standard, using machine
learning technology to model the background, and detecting the object from image or video…

… development of big data and artificial intelligence, data intelligence … : Data, algorithms, and
scenarios. We discuss the hot topics, growing trends, as well as research challenges in data …

… Deep learning based classification for paddy pests & diseases recognition. Proceedings
of 2018 International Conference on Mathematics and Artificial Intelligence. Chengdu,China, …

… In this thesis, we propose a novel hierarchical learning-based … , the RL applications in push
recovery control problems on … of requirement big data for learning-based approaches that …

… to leverage unobstrusive, big data to answer new questions, … from data science (machine
learning-based, content analysis, … non-obtrusive data to unravel the efficacy of and/or problems …

… survey of approaches and techniques in deep learning-based human activity analysis. In …
For self-supervised learning, we present a novel pretext task for self-supervised learning-based …

… -temporal data and various challenges in analyzing such data, … A deep-learning-based
forecasting ensemble to predict … location recommendation based on urban big data. In Proc. the …