October). Development of a UAV-type jellyfish monitoring system using deep learning, IEEE (2015), pp. 495-497 Google Scholar Kyrkou et al., 2018 C. Kyrkou, G. Plastiras, S. Venieris, T. Theocharides, C.-.S. Bouganis DroNet: Efficient convolutional neural network detector for real-ti...
Applying deep learning algorithm to maintain social distance in public place through drone technology Int. J. Perv. Comput. Commun. (2020) Google Scholar Reinecke and Prinsloo, 2017 M. Reinecke, T. Prinsloo The influence of drone monitoring on crop health and harvest size ...
A Deep Reinforcement Learning Approach to Efficient Drone Mobility Support The growing deployment of drones in a myriad of applications relies on seamless and reliable wireless connectivity for safe control and operation of drones. Cellular technology is a key enabler for providing essential wireless ...
can play a crucial role in critical drone monitoring applications like landmine detection.By processing data locally on a nearby edge server,edge computing can reduce communication latency and bandwidth requirements,allowing real-time analysis of magnetic field data.It enables faster decision-making and ...
* 其他: Preprint submitted to Epilepsy & Behavior, NEWroscience 2023* 题目: Unmasking Deepfake Faces from Videos Using An Explainable Cost-Sensitive Deep Learning Approach* PDF: arxiv.org/abs/2312.1074* 作者: Faysal Mahmud,Yusha Abdullah,Minhajul Islam,Tahsin Aziz* 相关: github.com/Faysal-MD/...
. All the models were trained with two strategies. The first one is the generally used strategy to avoid over training of the model. For it, we used callbacks with ‘EarlyStopping’ function of Tensorflow (keras) for monitoring validation loss. Training process stops, once the set conditions ...
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual label
deep learning algorithms on top of ultra-low power embedded computation nodes, like a miniaturized drone, and then weautomated the whole process. Our novel methodology allowed us first to deploy DroNet on thePULP-Shield, and then demonstrating how it enables the execution the CNN on board the ...
To ensure the Quality of Service (QoS) of such applications and Quality of Experience (QoE) for the end-users, it is necessary to employ a comprehensive monitoring approach. Requirement analysis is a key software engineering task in the whole lifecycle of applications; however, the requirements ...
Further, the location information can be used in different services including navigation, tracking, monitoring, etc. Location information, currently, is an important feature in most IoT applications. Besides this, recent advanced technologies have the ability to provide various options to make sure ...