Results 1 - 10 of 4,547

Architectural Styles and the Design of Network-based Software Architectures

by Roy Thomas Fielding , 2000
"... The World Wide Web has succeeded in large part because its software architecture has been designed to meet the needs of an Internet-scale distributed hypermedia system. The Web has been iteratively developed over the past ten years through a series of modifications to the standards that define its ..."
Abstract - Cited by 1119 (1 self) - Add to MetaCart
defines a framework for understanding software architecture via architectural styles and demonstrates how styles can be used to guide the architectural design of network-based application software. A survey of architectural styles for network-based applications is used to classify styles according

Classifier fitness based on accuracy

by Stewart W. Wilson - Evolutionary Computation , 1995
"... In many classifier systems, the classifier strength parameter serves as a predictor of future payoff and as the classifier’s fitness for the genetic algorithm. We investigate a classifier system, XCS, in which each classifier maintains a prediction of expected payoff, but the classifier’s fitness is ..."
Abstract - Cited by 350 (17 self) - Add to MetaCart
. Further, XCS tends to evolve classifiers that are maximally general, subject to an accuracy criterion. Besides introducing a new direction for classifier system research, these properties of XCS make it suitable for a wide range of reinforcement learning situations where generalization over states

Gradient-based learning applied to document recognition

by Yann Lecun, Léon Bottou, Yoshua Bengio, Patrick Haffner - Proceedings of the IEEE , 1998
"... Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradientbased learning technique. Given an appropriate network architecture, gradient-based learning algorithms can be used to synthesize a complex decision surface that can classify hi ..."
Abstract - Cited by 1533 (84 self) - Add to MetaCart
Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradientbased learning technique. Given an appropriate network architecture, gradient-based learning algorithms can be used to synthesize a complex decision surface that can classify

Example-based learning for view-based human face detection

by Kah-kay Sung, Tomaso Poggio - IEEE Transactions on Pattern Analysis and Machine Intelligence , 1998
"... Abstract—We present an example-based learning approach for locating vertical frontal views of human faces in complex scenes. The technique models the distribution of human face patterns by means of a few view-based “face ” and “nonface ” model clusters. At each image location, a difference feature v ..."
Abstract - Cited by 690 (24 self) - Add to MetaCart
Abstract—We present an example-based learning approach for locating vertical frontal views of human faces in complex scenes. The technique models the distribution of human face patterns by means of a few view-based “face ” and “nonface ” model clusters. At each image location, a difference feature

A Bayesian computer vision system for modeling human interactions

by Nuria M. Oliver, Barbara Rosario, Alex P. Pentland - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2000
"... We describe a real-time computer vision and machine learning system for modeling and recognizing human behaviors in a visual surveillance task [1]. The system is particularly concerned with detecting when interactions between people occur and classifying the type of interaction. Examples of interes ..."
Abstract - Cited by 538 (6 self) - Add to MetaCart
different state-based learning architectures, namely, HMMs and CHMMs for modeling behaviors and interactions. The CHMM model is shown to work much more efficiently and accurately. Finally, to deal with the problem of limited training data, a synthetic ªAlife-styleº training system is used to develop

Rapid object detection using a boosted cascade of simple features

by Paul Viola, Michael Jones - ACCEPTED CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION 2001 , 2001
"... This paper describes a machine learning approach for visual object detection which is capable of processing images extremely rapidly and achieving high detection rates. This work is distinguished by three key contributions. The first is the introduction of a new image representation called the " ..."
Abstract - Cited by 3283 (9 self) - Add to MetaCart
the "Integral Image" which allows the features used by our detector to be computed very quickly. The second is a learning algorithm, based on AdaBoost, which selects a small number of critical visual features from a larger set and yields extremely efficient classifiers[6]. The third contribution

Robust Real-time Object Detection

by Paul Viola, Michael Jones - International Journal of Computer Vision , 2001
"... This paper describes a visual object detection framework that is capable of processing images extremely rapidly while achieving high detection rates. There are three key contributions. The first is the introduction of a new image representation called the “Integral Image ” which allows the features ..."
Abstract - Cited by 1184 (4 self) - Add to MetaCart
used by our detector to be computed very quickly. The second is a learning algorithm, based on AdaBoost, which selects a small number of critical visual features and yields extremely efficient classifiers [6]. The third contribution is a method for combining classifiers in a “cascade ” which allows

Training Algorithms for Linear Text Classifiers

by David Lewis, Robert E. Schapire, James P. Callan, Ron Papka , 1996
"... Systems for text retrieval, routing, categorization and other IR tasks rely heavily on linear classifiers. We propose that two machine learning algorithms, the Widrow-Hoff and EG algorithms, be used in training linear text classifiers. In contrast to most IR methods, theoretical analysis provides pe ..."
Abstract - Cited by 276 (12 self) - Add to MetaCart
Systems for text retrieval, routing, categorization and other IR tasks rely heavily on linear classifiers. We propose that two machine learning algorithms, the Widrow-Hoff and EG algorithms, be used in training linear text classifiers. In contrast to most IR methods, theoretical analysis provides

A general framework for object detection

by Constantine P. Papageorgiou, Michael Oren, Tomaso Poggio - Sixth International Conference on , 1998
"... This paper presents a general trainable framework for object detection in static images of cluttered scenes. The detection technique we develop is based on a wavelet representation of an object class derived from a statistical analysis of the class instances. By learning an object class in terms of ..."
Abstract - Cited by 395 (21 self) - Add to MetaCart
previous approaches, this system learns from examples and does not rely on any a priori (handcrafted) models or motion-based segmentation. The paper also presents a motion-based extension to enhance the performance of the detection algorithm over video sequences. The results presented here suggest

Learning Rules that Classify E-Mail

by William W. Cohen - Proceedings of the 1996 AAAI Spring Symposium on Machine Learning and Information Access , 1996
"... wcohen~research.att.com Two methods for learning text classifiers are compared on classification problems that might arise in filtering and filing personM e-mail messages: a "traxiitionM IR " method based on TF-IDF weighting, and a new method for learning sets of "keyword-spotting rul ..."
Abstract - Cited by 198 (3 self) - Add to MetaCart
wcohen~research.att.com Two methods for learning text classifiers are compared on classification problems that might arise in filtering and filing personM e-mail messages: a "traxiitionM IR " method based on TF-IDF weighting, and a new method for learning sets of "
Results 1 - 10 of 4,547