Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Maja Rudinac"'
Autor:
Branimir Reljin, Irini Reljin, Nikola Reljin, Stevan Rudinac, Maja Rudinac, Vladan Radosavljević, Goran Zajić, Nenad Kojić
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2007 (2007)
Content-based image retrieval (CBIR) system with relevance feedback, which uses the algorithm for feature-vector (FV) dimension reduction, is described. Feature-vector reduction (FVR) exploits the clustering of FV components for a given query. Cluste
Externí odkaz:
https://doaj.org/article/0fb9d0b3f45e462ca300fb94b086e0fa
We present a new approach to population health where data-driven predictive models are learned for various stigmatized, underserved, and neglected chronic conditions that affect women. Our approach enables early detection within large populations at
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4279db1a4e50da0d36f8a3a769cf0bbe
https://doi.org/10.21203/rs.3.rs-2670098/v1
https://doi.org/10.21203/rs.3.rs-2670098/v1
Publikováno v:
VISIGRAPP (4: VISAPP)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b23c7bd88877d0b09af59f024471c250
https://doi.org/10.5220/0005677903170327
https://doi.org/10.5220/0005677903170327
Multimodal joint visual attention model for natural human-robot interaction in domestic environments
Publikováno v:
IROS
In this paper, we introduce a non-verbal multimodal joint visual attention model for human-robot interaction in household scenarios. Our model combines the bottom-up saliency and depth-based segmentation with the top-down cues such as pointing and ga
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8756ae4dc03fa69da96ba867332ecec5
https://doi.org/10.1109/iros.2015.7353703
https://doi.org/10.1109/iros.2015.7353703
Publikováno v:
MVA
Frequent and more accurate water level measurement will allow for a more efficient distribution of water, resulting in less water loss. Therefore in this paper we propose a novel method for accurate water level detection and measurement applied on im
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::02d72554aa41ef74382e69803e93df00
https://doi.org/10.1109/mva.2015.7153102
https://doi.org/10.1109/mva.2015.7153102
Publikováno v:
MVA
In this paper we tackle the challenges of visual tracking for personal robots. We have proposed a novel track-by-detection method that combines a semantic object model with depth properties to obtain target contours. The tracking can be initialized b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f339831d31aba8885092140e93810f20
https://doi.org/10.1109/mva.2015.7153207
https://doi.org/10.1109/mva.2015.7153207
Publikováno v:
Humanoids
In this paper we focus on a perception system for cognitive interaction between robots and humans especially for learning to recognize objects in household environments. Therefore we propose a novel three layered framework for object learning to brid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::52d382303f981643745454d49a7481d5
https://doi.org/10.1109/humanoids.2014.7041340
https://doi.org/10.1109/humanoids.2014.7041340
Publikováno v:
ICAR
For human-robot interaction users have to be robustly identified and their appearances learned online. Existing state of the art methods for face recognition do not support online learning of faces and lack the recognition performance required to be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76734074e8bd75cc233c99a50b7ac977
https://doi.org/10.1109/icar.2013.6766498
https://doi.org/10.1109/icar.2013.6766498
Publikováno v:
ICARCV
Extensive research has been conducted in the domain of object tracking. Among the existing tracking methods, most of them mainly focus on using various cues such as color, texture, contour, features, motion as well as depth information to achieve a r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eb1429b01b3f47cabe886987fb2c6ad9
https://doi.org/10.1109/icarcv.2012.6485305
https://doi.org/10.1109/icarcv.2012.6485305
Publikováno v:
IROS
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2012. IEEE Xplore
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2012
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2012. IEEE Xplore
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2012
In this paper, we present a unifying approach for learning and recognition of objects in unstructured environments through exploration. Taking inspiration from how young infants learn objects, we establish four principles for object learning. First,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::96c56197eaed52c45fba28e07aff7868
https://doi.org/10.1109/iros.2012.6385895
https://doi.org/10.1109/iros.2012.6385895