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21,480
Image Quality Assessment: From Error Visibility to Structural Similarity
- IEEE TRANSACTIONS ON IMAGE PROCESSING
, 2004
"... Objective methods for assessing perceptual image quality have traditionally attempted to quantify the visibility of errors between a distorted image and a reference image using a variety of known properties of the human visual system. Under the assumption that human visual perception is highly adapt ..."
Abstract
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Cited by 1499 (114 self)
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Objective methods for assessing perceptual image quality have traditionally attempted to quantify the visibility of errors between a distorted image and a reference image using a variety of known properties of the human visual system. Under the assumption that human visual perception is highly
Bandera: Extracting Finite-state Models from Java Source Code
- IN PROCEEDINGS OF THE 22ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING
, 2000
"... Finite-state verification techniques, such as model checking, have shown promise as a cost-effective means for finding defects in hardware designs. To date, the application of these techniques to software has been hindered by several obstacles. Chief among these is the problem of constructing a fini ..."
Abstract
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Cited by 654 (33 self)
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finite-state model that approximates the executable behavior of the software system of interest. Current best-practice involves handconstruction of models which is expensive (prohibitive for all but the smallest systems), prone to errors (which can result in misleading verification results
Interface Automata with Error States
, 2012
"... Abstract. De Alfaro and Henzinger advocated interface automata to model and study behavioural types, which describe communication patterns of systems while abstracting e.g. from data. They come with a specific parallel composition: if, in some state, one component tries to make an output, which the ..."
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the other one cannot receive, the state is regarded as an error. Error states are removed along with some states leading to them. As refinement relation an alternating simulation is introduced. In this report, we study to what degree this refinement relation is justified by the desires to avoid error states
How much should we trust differences-in-differences estimates?
, 2003
"... Most papers that employ Differences-in-Differences estimation (DD) use many years of data and focus on serially correlated outcomes but ignore that the resulting standard errors are inconsistent. To illustrate the severity of this issue, we randomly generate placebo laws in state-level data on femal ..."
Abstract
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Cited by 828 (1 self)
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Most papers that employ Differences-in-Differences estimation (DD) use many years of data and focus on serially correlated outcomes but ignore that the resulting standard errors are inconsistent. To illustrate the severity of this issue, we randomly generate placebo laws in state-level data
Range-Free Localization Schemes for Large Scale Sensor Networks
, 2003
"... Wireless Sensor Networks have been proposed for a multitude of location-dependent applications. For such systems, the cost and limitations of hardware on sensing nodes prevent the use of range-based localization schemes that depend on absolute point-to-point distance estimates. Because coarse accura ..."
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Cited by 525 (8 self)
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performs best when an irregular radio pattern and random node placement are considered, and low communication overhead is desired. We compare our work via extensive simulation, with three state-of-the-art range-free localization schemes to identify the preferable system configurations of each. In addition
Model Checking Programs
, 2003
"... The majority of work carried out in the formal methods community throughout the last three decades has (for good reasons) been devoted to special languages designed to make it easier to experiment with mechanized formal methods such as theorem provers, proof checkers and model checkers. In this pape ..."
Abstract
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Cited by 592 (63 self)
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, slicing, abstraction, and runtime analysis techniques to reduce the state space. JPF has been applied to a real-time avionics operating system developed at Honeywell, illustrating an intricate error, and to a model of a spacecraft controller, illustrating the combination of abstraction, runtime analysis
Imagenet classification with deep convolutional neural networks.
- In Advances in the Neural Information Processing System,
, 2012
"... Abstract We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes. On the test data, we achieved top-1 and top-5 error rates of 37.5% and 17.0% which is considerably better than the pr ..."
Abstract
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Cited by 1010 (11 self)
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Abstract We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes. On the test data, we achieved top-1 and top-5 error rates of 37.5% and 17.0% which is considerably better than
Incorporating non-local information into information extraction systems by Gibbs sampling
- IN ACL
, 2005
"... Most current statistical natural language processing models use only local features so as to permit dynamic programming in inference, but this makes them unable to fully account for the long distance structure that is prevalent in language use. We show how to solve this dilemma with Gibbs sampling, ..."
Abstract
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Cited by 730 (25 self)
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use this technique to augment an existing CRF-based information extraction system with long-distance dependency models, enforcing label consistency and extraction template consistency constraints. This technique results in an error reduction of up to 9 % over state-of-the-art systems on two
Reinforcement learning: a survey
- Journal of Artificial Intelligence Research
, 1996
"... This paper surveys the field of reinforcement learning from a computer-science perspective. It is written to be accessible to researchers familiar with machine learning. Both the historical basis of the field and a broad selection of current work are summarized. Reinforcement learning is the problem ..."
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Cited by 1714 (25 self)
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is the problem faced by an agent that learns behavior through trial-and-error interactions with a dynamic environment. The work described here has a resemblance to work in psychology, but differs considerably in the details and in the use of the word "reinforcement." The paper discusses central issues
An Introduction to the Kalman Filter
- UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL
, 1995
"... In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discrete-data linear filtering problem. Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of extensive research and application, particularly in the area o ..."
Abstract
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Cited by 1146 (13 self)
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of autonomous or assisted navigation.
The Kalman filter is a set of mathematical equations that provides an efficient computational (recursive) means to estimate the state of a process, in a way that minimizes the mean of the squared error. The filter is very powerful in several aspects: it supports
Results 1 - 10
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21,480
