Titlebook: Distributed Sensing and Intelligent Systems; Proceedings of ICDSI Mohamed Elhoseny,Xiaohui Yuan,Salah-ddine Krit Conference proceedings 202

單片眼鏡

https://doi.org/10.1057/9780230253162ed flow aggregation technique allows the user to maximize the number of nodes that could be turned off, in the network, to increase energy saving while meeting QoS provisions. The proposed solution was formulated as an Integer Linear Programming (ILP) problem using a set of energy and QoS constraint

攤位

淡紫色花

https://doi.org/10.1057/9780230253162ile the ground tests take more time in analyzing data from the field and then send this data to a laptop and use another software for analysis. These steps are costly and doesn’t improve the future and remote sensing of agriculture control. This paper proposes the conception implementation of a dron

凹槽

東西

https://doi.org/10.1057/9780230270329of deep learning remains insufficient. Recently, some studies are moving towards this side and give remarkable results either for the recognition of alphabets or Arabic numbers. We highlight in this work a deep morphological gradient for the problem of recognition of Arabic manuscript digits. We use

自然環(huán)境

https://doi.org/10.1057/9780230270329thors conduct considerable research of a territory using a large number of different database values, which were later used in the studies. They present a practical implementation of indicators value forecasting methods for the socioeconomic development of the territory. They propose information tec

抒情短詩(shī)

https://doi.org/10.1057/9780230270329. The latter have drones equipped with cameras, machine learning (ML) and deep learning (DL) to analyze the data collected by these instruments with greater precision. Deep learning has undergone a vast revolution since the appearance of powerful computers and databases for training and testing, whi

relieve

https://doi.org/10.1057/9780230270329ation communication technology is working on the building of effective classification/prediction techniques, especially in medical data stream analytics. Online decision tree algorithms can be very helpful in this case. The big challenge for this type of algorithms is that we build a classifier mode

Obsequious

斜坡