Deep Neural Networks: A Comparison on Different Computing Platforms
| Autor: | Alberto Quattrini Li, Ioannis Rekleitis, Modasshir |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Network architecture
Artificial neural network Computer science business.industry Robotics 02 engineering and technology 010501 environmental sciences USable Underwater robotics 01 natural sciences Object detection Domain (software engineering) Computer engineering 0202 electrical engineering electronic engineering information engineering Robot 020201 artificial intelligence & image processing Artificial intelligence business 0105 earth and related environmental sciences |
| Zdroj: | CRV |
| DOI: | 10.1109/crv.2018.00060 |
| Popis: | Deep Neural Networks (DNN) have gained tremendous popularity over the last years for several computer vision tasks, including classification and object detection. Such techniques have been able to achieve human-level performance in many tasks and have produced results of unprecedented accuracy. As DNNs have intense computational requirements in the majority of applications, they utilize a cluster of computers or a cutting edge Graphical Processing Unit (GPU), often having excessive power consumption and generating a lot of heat. In many robotics applications the above requirements prove to be a challenge, as there is limited power on-board and heat dissipation is always a problem. In particular in underwater robotics with limited space, the above two requirements have been proven prohibitive. As first of this kind, this paper aims at analyzing and comparing the performance of several state-of-the-art DNNs on different platforms. With a focus on the underwater domain, the capabilities of the Jetson TX2 from NVIDIA and the Neural Compute Stick from Intel are of particular interest. Experiments on standard datasets show how different platforms are usable on an actual robotic system, providing insights on the current state-of-the-art embedded systems. Based on such results, we propose some guidelines in choosing the appropriate platform and network architecture for a robotic system. |
| Databáze: | OpenAIRE |
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