Results 141 to 150 of about 1,177,560 (190)

Artificial sparse neuron dendrites for visual information inference. [PDF]

Sci Adv
Wang R, Liu G, Wang S, Jing X, Sun J, Li D, Ge K, Shen X, Qiu M, Wang H, Zhu B.   +10 more
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NeRF-Based Three-Dimensional Reconstruction for Large-Diameter Rescue Shafts. [PDF]

Sensors (Basel)
Gu H, Wang J, Chen C, Yang W, Ahamed M, Zou Z.   +5 more
europepmc   +1 more source

A Physics-Informed Multi-Task Soft Sensor for Uncertainty-Aware Slag Tin Content Prediction in Top-Blown Tin Smelting. [PDF]

Sensors (Basel)
Ma Z, Peng J, Zhou X, Xie K, Zhang Z.
europepmc   +1 more source

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Challenges in Sparse Image Reconstruction

International Journal of Image and Graphics, 2020
Handling huge amount of data from different sources more so in the images is the latest challenge. One of the solutions to this is sparse representation. The idea of sparsity has been receiving much attention recently from many researchers in the areas such as satellite image processing, signal processing, medical image processing, microscopy image ...
S. Shashi Kiran, K. V. Suresh 0001
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On the Sparse Reconstruction of Gene Networks

Journal of Computational Biology, 2008
We discuss a heuristic method for the sparse reconstruction of gene networks. The method is based on iterative greedy algorithms, and uses gene expression data from microarray experiments. Also, we show numerically that the greedy algorithms are able to give good approximative solutions to the sparse reconstruction problem even in the presence of ...
Mircea Andrecut, Stuart A. Kauffman
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Nonlocal Elastica Model for Sparse Reconstruction

Journal of Mathematical Imaging and Vision, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Mengyuan Yan, Yuping Duan
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Sparse reconstruction of ISOMAP representations

Journal of Intelligent & Fuzzy Systems, 2019
Isometric feature mapping (ISOMAP) is one of the classical methods of nonlinear dimensionality reduction (NLDR) and seeks for low dimensional (LD) structure of high dimensional (HD) data. However, the inverse problem of ISOMAP has never been investigated, which recovers the HD sample from the related LD sample, and its application prospect in data ...
Honggui Li, Maria Trocan
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Sparse correlation kernel reconstruction

1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258), 1999
This paper presents a new paradigm for signal reconstruction and superresolution, correlation kernel analysis (CKA), that is based on the selection of a sparse set of bases from a large dictionary of class-specific basis functions. The basis functions that we use are the correlation functions of the class of signals we are analyzing.
Constantine Papageorgiou, Federico Girosi, Tomaso A. Poggio   +2 more
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A recursive approach to reconstruction of sparse signals

2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014
Compressive Sensing (CS) theory details how a sparsely represented signal in a known basis can be reconstructed using less number of measurements. In many practical systems, the observation signal has a sparse representation in a continuous parameter space. This situation rises the possibility of use of the CS reconstruction techniques in the practical
Oguzhan Teke, Orhan Arikan, Ali Cafer Gürbüz   +2 more
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Sparse reconstruction for radar

SPIE Proceedings, 2008
Imaging is not itself a system goal, but is rather a means to support inference tasks. For data processing with linearized signal models, we seek to report all high-probability interpretations of the data and to report confidence labels in the form of posterior probabilities.
Lee C. Potter, Philip Schniter, Justin Ziniel   +2 more
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