Open Access Open Access  Restricted Access Subscription or Fee Access

Robust Neural Network-Based Object Detection Method for Drone Images

Marina Moseva, Kamil Kharrasov, Mikhail Gorodnichev

Abstract



Currently, existing detection systems have a number of shortcomings, including limitations in accuracy, speed of response, and ability to operate in difficult conditions (e.g., poor weather or visibility). These problems can lead to detection and positioning errors and, as a result, potential losses. The goal of this work is to improve the quality of pattern recognition at a distance in severe weather conditions in the context of applications on low power devices in various industries. To solve this problem, a method based on a combination of Deep Image Prior algorithmic image processing and YOLOv8 convolutional neural network is presented.

Keywords


Robustness, dehazing, convolution neural network, classification, deep image prior, pattern recognition.

Full Text:

PDF


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information. Also: DOI is paid service which provided by a third party. We never mentioned that we go for this for our any journal. However, journal have no objection if author go directly for this paid DOI service.