Complete Visualisation, Network Modeling and Training, Web Based Tool, for the Yolo Deep Neural Network Model in the Darknet Framework
| Autor: | Eduard Barnoviciu, Veta Ghenescu, Marian Ghenescu, Serban Carata, Mihai Chindea, Roxana Mihaescu |
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| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Artificial neural network Computer science Interface (computing) Darknet 02 engineering and technology computer.software_genre Object detection Field (computer science) Visualization 020901 industrial engineering & automation Feature (computer vision) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Data mining computer Network model |
| Zdroj: | ICCP |
| DOI: | 10.1109/iccp48234.2019.8959758 |
| Popis: | This paper presents an interface designed for the Darknet neural network, used by the state of the art YOLO (You Only Look Once) models. The object detection is still representing a challenge in the field of computer vision, and this interface has the main purpose of providing a way to generate more easily new networks, in order to obtain the desired object detection system. Furthermore, through this interface, it can be generated and displayed the feature maps at any point in the network. Therefore, the Darknet interface presented in this paper, leads to a better understanding of how a neural network makes a certain decision regarding the final predictions. And so, newer and better algorithms can be developed, in order to solve the object detection problem. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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