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Applications of entropic spanning graphs
IEEE Signal Processing Magazine - Tập 19 Số 5 - Trang 85-95 - 2002
A.O. Hero, Bing Ma, O.J.J. Michel, J. Gorman
This article presents applications of entropic spanning graphs to imaging and feature clustering applications. Entropic spanning graphs span a set of feature vectors in such a way that the normalized spanning length of the graph converges to the entropy of the feature distribution as the number of random feature vectors increases. This property makes these graphs naturally suited to applications w... hiện toàn bộ
#Entropy #Indexing #Image converters #Image registration #Information systems #Software libraries #Biomedical imaging #Information processing #Information retrieval #Content based retrieval
Locating the nodes: cooperative localization in wireless sensor networks
IEEE Signal Processing Magazine - Tập 22 Số 4 - Trang 54-69 - 2005
Neal Patwari, Joshua N. Ash, Spyros Kyperountas, Alfred O. Hero, Randolph L. Moses, N.S. Correal
Athanasios Papoulis: Longtime professor and noted author [Obituary]
IEEE Signal Processing Magazine - Tập 19 Số 5 - Trang 12-14 - 2002
Athanasios Papoulis, of Polytechnic University, Brooklyn, NY, a prominent author and passionate educator for four decades, died 25 April in Huntington, Long Island, New York, USA. He was 81. Papoulis distinguished himself in the scientific community for his more than 150 scholarly papers and nine books, including the classic Probability, Random Variables and Stochastic Processes, first published i... hiện toàn bộ
#Obituary #Papoulis #Athanasios
Understanding the Basis of the Kalman Filter Via a Simple and Intuitive Derivation [Lecture Notes]
IEEE Signal Processing Magazine - Tập 29 Số 5 - Trang 128-132 - 2012
Ramsey Faragher
Stochastic models for capturing image variability
IEEE Signal Processing Magazine - Tập 19 Số 5 - Trang 63-76 - 2002
A. Srivastava
We review a result in modeling lower order (univariate and bivariate) probability densities of pixel values resulting from bandpass filtering of images. Assuming an object-based model for images, a parametric family of probabilities, called Bessel K forms, has been derived (Grenander and Srivastava 2001). This parametric family matches well with the observed histograms for a large variety of image... hiện toàn bộ
#Stochastic processes #Band pass filters #Gabor filters #Object recognition #Pixel #Filtering #Histograms #Infrared imaging #Matched filters #Laplace equations
Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
IEEE Signal Processing Magazine - Tập 29 Số 6 - Trang 82-97 - 2012
Geoffrey E. Hinton, Li Deng, Dong Yu, George E. Dahl, Abdelrahman Mohamed, Navdeep Jaitly, Andrew Senior, Vincent Vanhoucke, Patrick Nguyen, Tara N. Sainath, Brian Kingsbury
Single-pixel imaging via compressive sampling
IEEE Signal Processing Magazine - Tập 25 Số 2 - Trang 83-91 - 2008
Marco F. Duarte, Mark A. Davenport, Dharmpal Takhar, Jason N. Laska, Ting Sun, Kevin F. Kelly, Richard G. Baraniuk
Deep Learning in Neuroimaging: Promises and challenges
IEEE Signal Processing Magazine - Tập 39 Số 2 - Trang 87-98 - 2022
Weizheng Yan, Gang Qu, Wenxing Hu, Anees Abrol, Biao Cai, Chen Qiao, Sergey M. Plis, Yu‐Ping Wang, Jing Sui, Vince D. Calhoun
Resampling Methods for Particle Filtering: Classification, implementation, and strategies
IEEE Signal Processing Magazine - Tập 32 Số 3 - Trang 70-86 - 2015
Tiancheng Li, Miodrag Bolić, Petar M. Djurić
Signal processing for hyperspectral image exploitation
IEEE Signal Processing Magazine - Tập 19 Số 1 - Trang 12-16 - 2002
Gary A. Shaw, Dimitris G. Manolakis
Tổng số: 49   
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