The recent progress in machine learning in computer vision guides to enormous hardware requirements. This paper discovers new innovative hardware capable of dealing with immense demands. The important decision is concentrating on task learning or the final classification. The main concern is on five domains: single-board computers, hardware accelerators, graphics cards, workstations, and cloud computing. These devices have several key features for detection that are discussed. Cloud computing is another presented approach. Furthermore, different delivery models of cloud computing are addressed
Research about deep learning applied in object detection tasks in LiDAR data has been massively wide...
peer reviewedSmart farming is one of the most diverse researches. In addition, the quantity of data ...
The object of research is to parallelize the learning process of artificial neural networks to autom...
The recent progress in machine learning in computer vision guides to enormous hardware requirements....
The rapid explosion of online Cloud-based services has put more pressure on Cloud service providers ...
This study investigates the capabilities and flexibility of edge devices for real-time data processi...
Nowadays, with the huge advance of sensor technology and the increase of the amount of data generate...
With the rise of machine learning and in particular deep learning entering all different types of fi...
Computer vision tasks such as image classification have prevalent use and are greatly aided by the d...
Modern machine learning (ML) applications are often deployed in the cloud environment to exploit the...
The first chapter serves as an introduction to our subject matter and elucidates the reasons why it ...
Cloud computing allows users and enterprises to process their data in high performance servers, thus...
In the last few years, we have witnessed an exponential growth in research activity into the advance...
Over the last years deep learning methods have been shown to outperform previous state-of-the-art ma...
GPU servers have been responsible for the recent improvements in the accuracy and inference speed of...
Research about deep learning applied in object detection tasks in LiDAR data has been massively wide...
peer reviewedSmart farming is one of the most diverse researches. In addition, the quantity of data ...
The object of research is to parallelize the learning process of artificial neural networks to autom...
The recent progress in machine learning in computer vision guides to enormous hardware requirements....
The rapid explosion of online Cloud-based services has put more pressure on Cloud service providers ...
This study investigates the capabilities and flexibility of edge devices for real-time data processi...
Nowadays, with the huge advance of sensor technology and the increase of the amount of data generate...
With the rise of machine learning and in particular deep learning entering all different types of fi...
Computer vision tasks such as image classification have prevalent use and are greatly aided by the d...
Modern machine learning (ML) applications are often deployed in the cloud environment to exploit the...
The first chapter serves as an introduction to our subject matter and elucidates the reasons why it ...
Cloud computing allows users and enterprises to process their data in high performance servers, thus...
In the last few years, we have witnessed an exponential growth in research activity into the advance...
Over the last years deep learning methods have been shown to outperform previous state-of-the-art ma...
GPU servers have been responsible for the recent improvements in the accuracy and inference speed of...
Research about deep learning applied in object detection tasks in LiDAR data has been massively wide...
peer reviewedSmart farming is one of the most diverse researches. In addition, the quantity of data ...
The object of research is to parallelize the learning process of artificial neural networks to autom...