Professional paper

https://doi.org/10.19279/TVZ.PD.2020-8-1-12

ENHANCING THE PERFORMANCE OF IMAGE PREPROCESSING FOR CLASSIFICATION AND OBJECT DETECTION

Ivan Cesar ; Zagreb University of Applied Sciences, Zagreb, Croatia
Valentin Solina ; Aether-signum Vrbovec, Croatia
Renata Kramberger ; Zagreb University of Applied Sciences, Zagreb, Croatia
Tin Kramberger ; Zagreb University of Applied Sciences, Zagreb, Croatia

Abstract

The image preprocessing optimization is a challenging task with numerous applications including classification and object detection on which this paper is oriented the most. Enhancing the performance in terms of processing time for image preprocessing is crucial to every researcher engaged into deep learning. A few common mistakes and practices are presented in this paper which can greatly impact training time, alongside practices and tools used for diagnosing potential pitfalls. In this paper, we evaluate several common Python libraries which are used for image preprocessing and analyze the impact of different augmentation ordering with respect to central processing unit (CPU) usage

Keywords

computer vision; deep learning; training optimization

Hrčak ID:

242763

URI

https://hrcak.srce.hr/242763

Publication date:

17.6.2020.

Article data in other languages: croatian

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