Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Matthew S. Keegan"'
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2010 (2010)
Given discrete event data, we wish to produce a probability density that can model the relative probability of events occurring in a spatial region. Common methods of density estimation, such as Kernel Density Estimation, do not incorporate geographi
Externí odkaz:
https://doaj.org/article/b3fb007bb9fb45b9a1a7f5e6d779e135
Publikováno v:
Inverse Problems & Imaging. 6:95-110
We propose a novel framework for energy-based multiphase segmentation over multiple channels. The framework allows the user to combine the information from each channel as the user sees fit, and thus allows the user to define how the information from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77f338e5d78a148fcf6ca1e898d06c52
https://doi.org/10.3934/ipi.2012.6.95
https://doi.org/10.3934/ipi.2012.6.95
Autor:
Rajan Bhattacharyya, Tom Goldstein, Kendrick Kay, Rachel Millin, Michael J. O'Brien, James Benvenuto, Matthew S. Keegan
Publikováno v:
2014 IEEE Signal Processing in Medicine and Biology Symposium (SPMB).
We present an algorithm, Sparse Atomic Feature Learning (SAFL), that transforms noisy labeled datasets into a sparse domain by learning atomic features of the underlying signal space via gradient minimization. The sparse signal representations are hi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::35d00733c0c0658876eeef0364b84a24
https://doi.org/10.1109/spmb.2014.7002972
https://doi.org/10.1109/spmb.2014.7002972
Publikováno v:
SPIE Proceedings.
In this paper we introduce two novel methods for application of `1-minimization. In the first method, sparse and low-rank decomposition and compressive sensing-based retrieval are combined and applied to a low power surveillance model. The method exp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a14719afaa84afcdb08d5801309d40fd
https://doi.org/10.1117/12.2024253
https://doi.org/10.1117/12.2024253
Autor:
Kevin R. Martin, Lei Zhang, Darrel J. VanBuer, Matthew S. Keegan, Deepak Khosla, David J. Huber
Publikováno v:
Proceedings of the 4th Workshop on Eye Gaze in Intelligent Human Machine Interaction.
In this paper, we describe a hybrid human-machine system for searching and detecting Objects of Interest (OI) in imagery. Automated methods for OI detection based on models of human visual attention have received much interest, but are inherently bot
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::674489a4a2a8cfee071f83fc68f550ed
https://doi.org/10.1145/2401836.2401837
https://doi.org/10.1145/2401836.2401837
Publikováno v:
ICMI
Though Electroencephalography (EEG)-based brain-computer interfaces (BCI) have come to outperform pure computer vision algorithms on difficult image triage tasks, none of these BCIs have leveraged the effects of motion on the human visual attention s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1518129b596e06df9bb3ef7466bf6f5b
https://doi.org/10.1145/2388676.2388800
https://doi.org/10.1145/2388676.2388800