Published 2020
| Version v1
Journal article
Comparative Performance Analysis of Neural Network Real-Time Object Detections in Different Implementations
- 1. OOO «Videointellect», Skolkovo Innovation Centre, 42 Bolshoy boulevard, 143026 Moscow (Russian Federation)
- 2. Institute of Experimental Physics, Slovak Academy of Sciences Watsonova 47, 04001 Košice (Slovakia)
- 3. The Laboratory of Information Technologies, JINR, 6 Joliot-Curie, 141980 Dubna, Moscow Region (Russian Federation)
Description
The performance of neural networks is one of the most important topics in the field of computer vision. In this work, we analyze the speed of object detection using the well-known YOLOv3 neural network architecture in different frameworks under different hardware requirements. We obtain results, which allow us to formulate preliminary qualitative conclusions about the feasibility of various hardware scenarios to solve tasks in real-time environments.
Availability note (English)
Available from https://www.epj-conferences.org/articles/epjconf/pdf/2020/02/epjconf_mmcp2019_02020.pdf; https://doaj.org/article/2661962922de47598c12dc31d48a9e6fAdditional details
Identifiers
Publishing Information
- Journal Title
- EPJ. Web of Conferences
- Journal Volume
- 226
- Journal Page Range
- vp.
- ISSN
- 2100-014X
Conference
- Title
- International Conference on Mathematical Modeling and Computational Physics
- Acronym
- MMCP 2019
- Dates
- 1-5 Jul 2019
- Place
- Stara Lesna (Slovakia)
INIS
- Country of Publication
- France
- Country of Input or Organization
- France
- INIS RN
- 53115745
- Subject category
- S97: MATHEMATICAL METHODS AND COMPUTING;
- Resource subtype / Literary indicator
- Conference
- Descriptors DEI
- COMPUTER ARCHITECTURE; COMPUTERS; DETECTION; IMPLEMENTATION; NEURAL NETWORKS; PERFORMANCE; VISION