Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Y. Vizilter"'
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B2-2020, Pp 583-588 (2020)
In this paper, we propose a new method for knowledge distilling based on generative adversarial networks. Discriminator CNNs is used as an adaptive knowledge distilling loss. In experiments, single shot multibox detector SSD based on MobileNet v2 and
Externí odkaz:
https://doaj.org/article/a371d91676f04c409cc83c89a1907c4a
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B2-2020, Pp 415-420 (2020)
The paper addresses the problem of a city heightmap restoration using satellite view image and some manually created area with 3D data. We propose the approach based on generative adversarial networks. Our algorithm contains three steps: low quality
Externí odkaz:
https://doaj.org/article/92c5b7792ab642de9eefc0fb1cd67ba8
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B2-2020, Pp 617-622 (2020)
This paper is devoted to the problem of image semantic segmentation for machine vision system of off-road autonomous robotic vehicle. Most modern convolutional neural networks require large computing resources that go beyond the capabilities of many
Externí odkaz:
https://doaj.org/article/4f728e7937d64aacbc5f8bfd58132cbb
Autor:
B. Vishnyakov, Y. Blokhinov, I. Sgibnev, V. Sheverdin, A. Sorokin, A. Nikanorov, P. Masalov, K. Kazakhmedov, S. Brianskiy, Е. Andrienko, Y. Vizilter
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B2-2020, Pp 637-644 (2020)
In this paper we describe a new multi-sensor platform for data collection and algorithm testing. We propose a couple of methods for solution of semantic scene understanding problem for land autonomous vehicles. We describe our approaches for automati
Externí odkaz:
https://doaj.org/article/886adcad550e4d5eae2392a8dc8d2a08
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-2, Pp 379-384 (2018)
In this paper we combine the ideas of image matching, object detection, image retrieval and zero-shot learning for stating and solving the semantic matching problem. Semantic matcher takes two images (test and request) as input and returns detected o
Externí odkaz:
https://doaj.org/article/9e937788d17d49019a0669cb5d6a781d
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XL-3, Pp 351-356 (2014)
This paper considers a statistical approach to define pseudo-moving (false) objects in video surveillance systems by constructing systems of hypothesis with the criteria based on statistical behavioral particularities. The obtained results are integr
Externí odkaz:
https://doaj.org/article/76da0894916b4b64af176700ecc67a5e
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XL-3, Pp 347-350 (2014)
In this paper a new approach for moving objects detection in video surveillance systems is proposed. It is based on iLBP (intensity local binary patterns) descriptor that combines the classic LBP (local binary patterns) and the multiple regressive ps
Externí odkaz:
https://doaj.org/article/0153617de7df4f9a97a9198cc6698f36
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXIX-B3, Pp 579-583 (2012)
This paper presents a motion detection and object tracking technique for digital video surveillance applications. Motion analysis algorithms are based on processing of multiple-regression pseudospectrums. Complete object detection and tracking schem
Externí odkaz:
https://doaj.org/article/584e89f7ceba4a00a2a1c246d40efbda
Conference
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Conference
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