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LabelMe: A Database and Web-Based Tool for Image Annotation

by B. C. Russell, A. Torralba, K. P. Murphy, W. T. Freeman , 2008
"... We seek to build a large collection of images with ground truth labels to be used for object detection and recognition research. Such data is useful for supervised learning and quantitative evaluation. To achieve this, we developed a web-based tool that allows easy image annotation and instant sha ..."
Abstract - Cited by 670 (47 self) - Add to MetaCart
recognition and detection. Also, we show how to extend the dataset to automatically enhance object labels with WordNet, discover object parts, recover a depth ordering of objects in a scene, and increase the number of labels using minimal user supervision and images from the web.

Semi-Supervised Learning Literature Survey

by Xiaojin Zhu , 2006
"... We review the literature on semi-supervised learning, which is an area in machine learning and more generally, artificial intelligence. There has been a whole spectrum of interesting ideas on how to learn from both labeled and unlabeled data, i.e. semi-supervised learning. This document is a chapter ..."
Abstract - Cited by 757 (8 self) - Add to MetaCart
We review the literature on semi-supervised learning, which is an area in machine learning and more generally, artificial intelligence. There has been a whole spectrum of interesting ideas on how to learn from both labeled and unlabeled data, i.e. semi-supervised learning. This document is a

Activity recognition from user-annotated acceleration data

by Ling Bao, Stephen S. Intille , 2004
"... In this work, algorithms are developed and evaluated to detect physical activities from data acquired using five small biaxial accelerometers worn simultaneously on different parts of the body. Acceleration data was collected from 20 subjects without researcher supervision or observation. Subjects ..."
Abstract - Cited by 492 (7 self) - Add to MetaCart
In this work, algorithms are developed and evaluated to detect physical activities from data acquired using five small biaxial accelerometers worn simultaneously on different parts of the body. Acceleration data was collected from 20 subjects without researcher supervision or observation

Heuristic Evaluation of User Interfaces

by Jukob Nielsen, Rolf Molich - IN: PROCEEDINGS OF THE CHI´90 CONFERENCE, SEATTLE , 1990
"... Heuristic evaluation is an informal method of usability analysis where a number of evaluators are presented with an interface design and asked to comment on it. Four ex-periments showed that individual evaluators were mostly quite bad at doing such heuristic evaluations and that they only found betw ..."
Abstract - Cited by 502 (4 self) - Add to MetaCart
Heuristic evaluation is an informal method of usability analysis where a number of evaluators are presented with an interface design and asked to comment on it. Four ex-periments showed that individual evaluators were mostly quite bad at doing such heuristic evaluations and that they only found between 20 and 51 % of the usability problems in the interfaces they evaluated. On the other hand, we could aggregate the evaluations from several evaluators to a single evaluation and such aggregates do rather well, even when they consist of only three to five people.

An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision

by Yuri Boykov, Vladimir Kolmogorov - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2001
"... After [10, 15, 12, 2, 4] minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in low-level vision. The combinatorial optimization literature provides many min-cut/max-flow algorithms with different polynomial time compl ..."
Abstract - Cited by 1311 (54 self) - Add to MetaCart
After [10, 15, 12, 2, 4] minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in low-level vision. The combinatorial optimization literature provides many min-cut/max-flow algorithms with different polynomial time

Convergent Tree-reweighted Message Passing for Energy Minimization

by Vladimir Kolmogorov - ACCEPTED TO IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (PAMI), 2006. ABSTRACTACCEPTED TO IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (PAMI) , 2006
"... Algorithms for discrete energy minimization are of fundamental importance in computer vision. In this paper we focus on the recent technique proposed by Wainwright et al. [33]- tree-reweighted max-product message passing (TRW). It was inspired by the problem of maximizing a lower bound on the energy ..."
Abstract - Cited by 491 (16 self) - Add to MetaCart
Algorithms for discrete energy minimization are of fundamental importance in computer vision. In this paper we focus on the recent technique proposed by Wainwright et al. [33]- tree-reweighted max-product message passing (TRW). It was inspired by the problem of maximizing a lower bound

The BSD Packet Filter: A New Architecture for User-level Packet Capture

by Steven Mccanne, Van Jacobson , 1992
"... Many versions of Unix provide facilities for user-level packet capture, making possible the use of general purpose workstations for network monitoring. Because network monitors run as user-level processes, packets must be copied across the kernel/user-space protection boundary. This copying can be m ..."
Abstract - Cited by 566 (2 self) - Add to MetaCart
Many versions of Unix provide facilities for user-level packet capture, making possible the use of general purpose workstations for network monitoring. Because network monitors run as user-level processes, packets must be copied across the kernel/user-space protection boundary. This copying can

A scaled conjugate gradient algorithm for fast supervised learning

by Martin F. Møller - NEURAL NETWORKS , 1993
"... A supervised learning algorithm (Scaled Conjugate Gradient, SCG) with superlinear convergence rate is introduced. The algorithm is based upon a class of optimization techniques well known in numerical analysis as the Conjugate Gradient Methods. SCG uses second order information from the neural netwo ..."
Abstract - Cited by 441 (0 self) - Add to MetaCart
A supervised learning algorithm (Scaled Conjugate Gradient, SCG) with superlinear convergence rate is introduced. The algorithm is based upon a class of optimization techniques well known in numerical analysis as the Conjugate Gradient Methods. SCG uses second order information from the neural

U-Net: A User-Level Network Interface for Parallel and Distributed Computing

by Thorsten Von Eicken, Anindya Basu, Vineet Buch, Werner Vogels - In Fifteenth ACM Symposium on Operating System Principles , 1995
"... The U-Net communication architecture provides processes with a virtual view of a network interface to enable userlevel access to high-speed communication devices. The architecture, implemented on standard workstations using offthe-shelf ATM communication hardware, removes the kernel from the communi ..."
Abstract - Cited by 596 (17 self) - Add to MetaCart
the communication path, while still providing full protection. The model presented by U-Net allows for the construction of protocols at user level whose performance is only limited by the capabilities of network. The architecture is extremely flexible in the sense that traditional protocols like TCP and UDP

NewsWeeder: Learning to Filter Netnews

by Ken Lang - in Proceedings of the 12th International Machine Learning Conference (ML95 , 1995
"... A significant problem in many information filtering systems is the dependence on the user for the creation and maintenance of a user profile, which describes the user's interests. NewsWeeder is a netnews-filtering system that addresses this problem by letting the user rate his or her interest l ..."
Abstract - Cited by 555 (0 self) - Add to MetaCart
A significant problem in many information filtering systems is the dependence on the user for the creation and maintenance of a user profile, which describes the user's interests. NewsWeeder is a netnews-filtering system that addresses this problem by letting the user rate his or her interest
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