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Neural Network Synthesis Using Cellular Encoding And The Genetic Algorithm
, 1994
"... Artificial neural networks used to be considered only as a machine that learns using small modifications of internal parameters. Now this is changing. Such learning method do not allow to generate big neural networks for solving real world problems. This thesis defends the following three points: f ..."
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Cited by 197 (5 self)
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network means a neural network that is made of several subnetworks, arranged in a hierarchical way. For example, the same subnetwork can be repeated. This thesis encompasses two parts. The first part demonstrates the second point. Cellular encoding is presented as a machine language for neural networks
Recovering 3D Human Pose from Monocular Images
"... We describe a learning based method for recovering 3D human body pose from single images and monocular image sequences. Our approach requires neither an explicit body model nor prior labelling of body parts in the image. Instead, it recovers pose by direct nonlinear regression against shape descrip ..."
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Cited by 261 (0 self)
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descriptor vectors extracted automatically from image silhouettes. For robustness against local silhouette segmentation errors, silhouette shape is encoded by histogramofshapecontexts descriptors. We evaluate several different regression methods: ridge regression, Relevance Vector Machine (RVM) regression
Model of human visualmotion sensing
, 1985
"... We propose a model of how humans sense the velocity of moving images. The model exploits constraints provided by human psychophysics, notably that motionsensing elements appear tuned for twodimensional spatial frequency, and by the frequency spectrum of a moving image, namely, that its support li ..."
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Cited by 249 (3 self)
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lies in the plane in which the temporal frequency equals the dot product of the spatial frequency and the image velocity. The first stage of the model is a set of spatialfrequencytuned, directionselective linear sensors. The temporal frequency of the response of each sensor is shown to encode
Semantic Encoding and Retrieval in the Left Inferior Prefrontal Cortex: A Functional MRI Study of Task Difficulty and Process Specificity
 Journal of Neuroscience
, 1995
"... Concrete Task), with a nonsemantic encoding task. In the first experiment, subjects alternately performed the semantic encoding task and a nonsemantic encoding task, in which subjects had to decide if words were printed in uppercase or lowercase letters (Uppercase/Lowercase Task). In the second expe ..."
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Cited by 167 (17 self)
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Concrete Task), with a nonsemantic encoding task. In the first experiment, subjects alternately performed the semantic encoding task and a nonsemantic encoding task, in which subjects had to decide if words were printed in uppercase or lowercase letters (Uppercase/Lowercase Task). In the second
Encoding program executions
 In ICSE
, 2001
"... Dynamic analysis is based on collecting data as the program runs. However, raw traces tend to be too voluminous and too unstructured to be used directly for visualization and understanding. We address this problem in two phases: the first phase selects subsets of the data and then compacts it, while ..."
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Cited by 101 (2 self)
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, while the second phase encodes the data in an attempt to infer its structure. Our major compaction/selection techniques include gprofstyle Ndepth call sequences, selection based on class, compaction based on time intervals, and encoding the whole execution as a directed acyclic graph. Our structure
The polyadic πcalculus: a tutorial
 LOGIC AND ALGEBRA OF SPECIFICATION
, 1991
"... The πcalculus is a model of concurrent computation based upon the notion of naming. It is first presented in its simplest and original form, with the help of several illustrative applications. Then it is generalized from monadic to polyadic form. Semantics is done in terms of both a reduction syste ..."
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Cited by 187 (1 self)
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, the equational validity of βconversion is proved with the help of replication theorems. The paper ends with an extension of the πcalculus to ωorder processes, and a brief account of the demonstration by Davide Sangiorgi that higherorder processes maybe faithfully encoded at firstorder. This extends
Automatically parcellating the human cerebral cortex.
 Cereb. Cortex
, 2004
"... Abstract We present a technique for automatically assigning a neuroanatomical label to each location on a cortical surface model based on probabilistic information estimated from Introduction Techniques for labeling geometric features of the cerebral cortex are useful for analyzing a variety of fu ..."
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Cited by 189 (14 self)
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first order anisotropic nonstationary Markov random field (MRF), allowing it to capture the spatial relationships between parcellation units that are present in the training set. The anisotropy separates label probabilities in the first and second principal curvature directions, in order to encode
Design of parallel concatenated convolutional codes
 IEEE Transactions on Communications
, 1996
"... Abstract. ’ parallel concatenated convolutional coding scheme consists of two constituent systematic convolutional encoders linked by an interleaver. The information bits at the input of the first encoder are scrambled by the interleaver before entering the second encoder. The codewords of the para ..."
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Cited by 130 (10 self)
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Abstract. ’ parallel concatenated convolutional coding scheme consists of two constituent systematic convolutional encoders linked by an interleaver. The information bits at the input of the first encoder are scrambled by the interleaver before entering the second encoder. The codewords
The Z_4linearity of Kerdock, Preparata, Goethals, and related codes
, 2001
"... Certain notorious nonlinear binary codes contain more codewords than any known linear code. These include the codes constructed by NordstromRobinson, Kerdock, Preparata, Goethals, and DelsarteGoethals. It is shown here that all these codes can be very simply constructed as binary images under the ..."
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Cited by 178 (15 self)
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are extended cyclic codes over ¡ 4, which greatly simplifies encoding and decoding. An algebraic harddecision decoding algorithm is given for the ‘Preparata ’ code and a Hadamardtransform softdecision decoding algorithm for the Kerdock code. Binary first and secondorder ReedMuller codes are also linear
An Analysis of the BurrowsWheeler Transform
 Journal of the ACM
, 2001
"... this paper we analyze two algorithms which use this technique. The first one is the original algorithm described by Burrows and Wheeler, which, despite its simplicity, outperforms the Gzip compressor. The second one uses an additional runlength encoding step to improve compression. We prove that th ..."
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Cited by 173 (13 self)
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this paper we analyze two algorithms which use this technique. The first one is the original algorithm described by Burrows and Wheeler, which, despite its simplicity, outperforms the Gzip compressor. The second one uses an additional runlength encoding step to improve compression. We prove
Results 11  20
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