Computer Vision in Cell Biology
https://doi.org/10.1016/j.cell.2011.11.001
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https://doi.org/10.1016/j.cell.2011.11.001
Fashion is the way we present ourselves to the world and has become one of the world’s largest industries. Fashion, mainly conveyed by vision, has thus attracted much attention from computer vision researchers in recent years. Given the rap...
https://doi.org/10.1145/3447239
This monograph by one of the world's leading vision researchers provides a thorough, mathematically rigorous exposition of a broad and vital area in computer vision: the problems and techniques related to three-dimensional (stereo) vision a...
Computer vision is a field that involves making a machine “see”. This technology uses a camera and computer instead of the human eye to identify, track and measure targets for further image processing. With the development of computer visio...
https://doi.org/10.1016/j.inpa.2019.09.006
https://doi.org/10.1007/978-3-642-15796-7_3
Contents of Volume One: Preface. Contributors. B. Jahne, Introduction. Illumination and Image Formation. H. Hausecker, Radiation. H. Hausecker, Interaction of Radiation with Matter. P. Geisler, Geometric and Wave Optics. H. Hausecker, Radio...
https://doi.org/10.1007/978-3-319-46448-0
https://doi.org/10.1007/978-0-387-31439-6
Abstract : The main contribution of this thesis is the development of a three dimensional geometric modeling system for application to computer vision. In computer vision geometric models provide a goal for descriptive image analysis, an or...
Recent years have witnessed enormous progress in AI-related fields such as computer vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it becomes increasingly difficult to stay up-to-date or enter the fiel...
https://doi.org/10.1561/0600000079
https://doi.org/10.1007/978-3-319-11550-4
https://doi.org/10.1007/0-387-28487-7
We introduce a method to train Binarized Neural Networks (BNNs) - neural networks with binary weights and activations at run-time and when computing the parameters' gradient at train-time. We conduct two sets of experiments, each based on a...
https://doi.org/10.48550/arxiv.1602.02505
From the Publisher: Discover the new, unconventional alternatives for conquering RF and microwave design and modeling problems using neural networks information processing systems that can learn, generalize, and even allow model developm...
Most current Artificial Neural Network (ANN) models are based on highly simplified brain dynamics. They have been used as powerful computational tools to solve complex pattern recognition, function estimation, and classification problems. A...
https://doi.org/10.1142/s0129065709002002
https://doi.org/10.1016/j.eswa.2009.02.073
Abstract. Over the past decade there have been considerable increases in both the quantity of remotely sensed data available and the use of neural networks. These increases have largely taken place in parallel, and it is only recently that ...
https://doi.org/10.1080/014311697218700
https://doi.org/10.1016/0005-1098(92)90053-i
The dynamics of the modified canonical nonlinear programming circuit are studied and how to guarantee the stability of the network's solution. By considering the total cocontent function, the solution of the canonical nonlinear programming ...
https://doi.org/10.1109/31.1783