Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Shvets, Mykhailo"'
Multi-task approaches to joint depth and segmentation prediction are well-studied for monocular images. Yet, predictions from a single-view are inherently limited, while multiple views are available in many robotics applications. On the other end of
Externí odkaz:
http://arxiv.org/abs/2311.00134
In this work, we propose "tangent images," a spherical image representation that facilitates transferable and scalable $360^\circ$ computer vision. Inspired by techniques in cartography and computer graphics, we render a spherical image to a set of d
Externí odkaz:
http://arxiv.org/abs/1912.09390
Designing new molecules with a set of predefined properties is a core problem in modern drug discovery and development. There is a growing need for de-novo design methods that would address this problem. We present MolecularRNN, the graph recurrent g
Externí odkaz:
http://arxiv.org/abs/1905.13372
Recently two-stage detectors have surged ahead of single-shot detectors in the accuracy-vs-speed trade-off. Nevertheless single-shot detectors are immensely popular in embedded vision applications. This paper brings single-shot detectors up to the sa
Externí odkaz:
http://arxiv.org/abs/1901.03353
While state-of-the-art general object detectors are getting better and better, there are not many systems specifically designed to take advantage of the instance detection problem. For many applications, such as household robotics, a system may need
Externí odkaz:
http://arxiv.org/abs/1803.04610
Publikováno v:
Microsystems, Electronics and Acoustics; Том 24, № 6 (2019); 17-21
Микросистемы, Электроника и Акустика; Том 24, № 6 (2019); 17-21
Мікросистеми, Електроніка та Акустика; Том 24, № 6 (2019); 17-21
Микросистемы, Электроника и Акустика; Том 24, № 6 (2019); 17-21
Мікросистеми, Електроніка та Акустика; Том 24, № 6 (2019); 17-21
The paper is devoted to the preparation and analysis of data sets in order to improve the prediction of the amount of consumed and generated electrical energy volumes using machine learning methods. The importance level and influence on predicting th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=scientific_p::828747c526acd7f4586743ee144afe41
http://elc.kpi.ua/article/view/186996
http://elc.kpi.ua/article/view/186996
