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Dipmeter and Borehole Image Log Technology
Borehole imaging is among the fastest and most accurate methods for collecting high resolution subsurface data. Recent breakthroughs in acquisition, tool design, and modeling software provide real-time subsurface images of incredible detail, from the drill bit straight to a workstation. This text portrays key applications of dipmeter and image log data across the exploration and production life cycle.
INNC 90 PARIS
Neural Networks have been the theater of a dramatic increase of activities in the last five years. The interest of mixing results from fields as different as neurobiology, physics (spin glass theory), mathematics (linear algebra, statistics ... ), computer science (software engineering, hardware architectures ... ) or psychology has attracted a large number of researchers to the field. The perspective of dramatic improvements in many applications has lead important companies to launch new neural network programs and start-ups have mushroomed to address this new market. Throughout the world large programs are being set-up: in Japan the government has committed more than $18 million per year t...
Pixelization Paradigm
This book constitutes the thoroughly refereed post-proceedings of the Visual Information Expert Workshop, VIEW 2006, held in Paris, France, in April 2006. The 23 revised full papers were carefully selected from numerous submissions during two rounds of reviewing and improvement. The book is categorized in three main parts: pixelization theory, pixelization applications, pixelization and cognition.
Random Matrix Methods for Machine Learning
This unified random matrix approach to large-dimensional machine learning covers applications from power detection to deep neural networks.
Implementation Techniques
This volume covers practical and effective implementation techniques, including recurrent methods, Boltzmann machines, constructive learning with methods for the reduction of complexity in neural network systems, modular systems, associative memory, neural network design based on the concept of the Inductive Logic Unit, and a comprehensive treatment of implementations in the area of data classification. Numerous examples enhance the text. Practitioners, researchers,and students in engineering and computer science will find Implementation Techniques a comprehensive and powerful reference. Key Features * Recurrent methods * Boltzmann machines * Constructive learning with methods for the reduction of complexity in neural network systems * Modular systems * Associative memory * Neural network design based on the concept of the Inductive Logic Unit * Data classification * Integrated neuron model systems that function as programmable rational approximators With numerous examples to enhance the text, practitioners, researchers, and students in engineering and computer science will find Implementation Techniques a uniquely comprehensive and powerful reference source
Morphological Image Processing: Architecture and VLSI design
Summary Based on the experiences of past designs and the outcome of recent studies in the comparisons of low-level image processing architectures, a pipelined system for real time low-image processing has been designed and realized in CMOS technology. To minimize design pitfalls, a study was performed to the details of the design solutions that have been found in embodimentsof the three main architectural groups of image processing; the Square Processor Arrays, the Linear Processor Arrays and the Pipelines. This is reflected in a theoretical model. As the design is based on bitplane-wise processing of images, research was performed on the principles ofCellularLogic Processing of two dimensional images. of binary A methodology has been developed that is based on the transformation images using sets of Hit-or-Miss masks. This method appeared to be extendable to higher dimensional images. A theoretical model for the generation of break-point conditions in high dimensional images has been developed, and applied up to dimension three.
Artificial Neural Networks - ICANN 96
This book constitutes the refereed proceedings of the sixth International Conference on Artificial Neural Networks - ICANN 96, held in Bochum, Germany in July 1996. The 145 papers included were carefully selected from numerous submissions on the basis of at least three reviews; also included are abstracts of the six invited plenary talks. All in all, the set of papers presented reflects the state of the art in the field of ANNs. Among the topics and areas covered are a broad spectrum of theoretical aspects, applications in various fields, sensory processing, cognitive science and AI, implementations, and neurobiology.
Petrophysics
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GeoArabia
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