Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Artem Korobov"'
Publikováno v:
Радіоелектронні і комп'ютерні системи, Vol 2024, Iss 3, Pp 55-66 (2024)
Neural network object detectors are increasingly being used for aerial video analysis, with a growing demand for onboard processing on UAVs and other limited resources. However, the vulnerability of neural networks to adversarial noise, out-of-distri
Externí odkaz:
https://doaj.org/article/fb0518b83e8c4af6909e2c785f31707d
Autor:
Artem Korobov, Viacheslav Moskalenko, Alona Sergiyvna Moskalenko, Yaroslav Kovalskyi, Mykola Zaretskyi
Publikováno v:
RADIOELECTRONIC AND COMPUTER SYSTEMS. :71-81
A machine learningsemi-supervised method was developed for the classification analysis of defects on the surface of the sewer pipe based on CCTV video inspection images. The aim of the research is the process of defect detection on the surface of sew
Publikováno v:
Eastern-European Journal of Enterprise Technologies, Vol 4, Iss 9 (94), Pp 19-26 (2018)
The model of object detector and the criterion of leaning effectiveness of the model were proposed. The model contains 7 first modules of the convolutional Squeezenet network, two convolutional multiscale layers and the informationextreme classifie
Publikováno v:
Eastern-European Journal of Enterprise Technologies. 5:26-33
We developed the algorithm of learning of the multilayer feature extractor based on ideas and methods of neural gas and sparse encoding, for the problem of prediction of violation of agreement conditions on the service level in a cloud-based environm
Publikováno v:
Radio Electronics, Computer Science, Control.
Context. Lightweight model and effective training algorithm of on-board object detection system for a compact drone are developed. The object of research is the process of small object detection on aerial images under computational resource constrain
Publikováno v:
Data
Volume 4
Issue 1
Volume 4
Issue 1
Trainable visual navigation systems based on deep learning demonstrate potential for robustness of onboard camera parameters and challenging environment. However, a deep model requires substantial computational resources and large labelled training s
Publikováno v:
Radio Electronics, Computer Science, Control.
Актуальність теми статті полягає в тому, що питання вибору оптимальних в інформаційному та вартісному сенсах моделей і методів аналізу
Autor:
Vyacheslav Zhurba, Alena Moskalenko, Oleg Berest, Artem Korobov, Volodymyr Nahornyi, Julia Zavgorodnya
Publikováno v:
2018 IEEE First International Conference on System Analysis & Intelligent Computing (SAIC).
Proposed method for the synthesis of information extreme classifier of images with rough binary encoding of sparse histogram of frequency of occurrence of visual words, to provide a computationally efficient decision rules by small volume dataset wit
Autor:
Serhii Serhiiovych Martynenko, Oleksandr Borovenskyi, Artem Korobov, Alona Moskalenko, Viacheslav Vasylovych Moskalenko, Olha Boiko
The paper presents a novel model of convolutional neural network for visual feature extraction, support vector machine for position prediction and information-extreme classifier for obstacle prediction with new training methods to build decision rule
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::583c6813b94542500aa37a7ff8be843a
https://ena.lpnu.ua/handle/ntb/52433
https://ena.lpnu.ua/handle/ntb/52433