Results 1 - 10 of 140

Information Leakage Detection in Bound-ary Ambients

by Chiara Braghin, Agostino Cortesi, Riccardo Focardi - In Proc. of Computing: The Australasian Theory Symposium (CATS'03). Electronic Notes in Theoretical Computer Science, Elsevier , 2001
"... A variant of Mobile Ambient Calculus is introduced, called Boundary Ambient, to model multilevel security policies. Ambients that may guarantee to properly protect their content are explicitly identified as boundaries: a boundary can be seen as a resource access manager for confidential data. In thi ..."
Abstract - Cited by 2 (1 self) - Add to MetaCart
A variant of Mobile Ambient Calculus is introduced, called Boundary Ambient, to model multilevel security policies. Ambients that may guarantee to properly protect their content are explicitly identified as boundaries: a boundary can be seen as a resource access manager for confidential data

Oriented Edge Forests for Boundary Detection

by Sam Hallman, Charless C. Fowlkes
"... We present a simple, efficient model for learning bound-ary detection based on a random forest classifier. Our ap-proach combines (1) efficient clustering of training exam-ples based on a simple partitioning of the space of local edge orientations and (2) scale-dependent calibration of in-dividual t ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
We present a simple, efficient model for learning bound-ary detection based on a random forest classifier. Our ap-proach combines (1) efficient clustering of training exam-ples based on a simple partitioning of the space of local edge orientations and (2) scale-dependent calibration of in

Secure and fault-tolerant event boundary detection in wireless sensor networks

by Kui Ren, Kai Zeng, Student Member, Wenjing Lou - IEEE Transactions on Wireless Communications , 2008
"... Abstract — Event boundary detection is in and of itself a useful application in wireless sensor networks (WSNs). Typically, it includes the detection of a large-scale spatial phenomenon such as the transportation front line of a contamination or the diagnosis of network health. In this paper, we pre ..."
Abstract - Cited by 12 (0 self) - Add to MetaCart
strength and performance of SEBD are evaluated by both analysis and simulations. Index Terms — Security, wireless sensor network, event bound-ary detection. I.

Pattern Recognition Methods for Object Boundary Detection

by Arnaldo J. Abrantesy, Jorge S. Marquesz, R. Conselheiro, Torre Norte, R. Rovisco Pais
"... Boundary extraction is a data representation problem: image features are segmented and approximated by a parametric curve or a sequence of model points. However, the use of classic Pattern Recognition methods in bound-ary detection is unusual when compared with more popular approaches, e.g., active ..."
Abstract - Add to MetaCart
Boundary extraction is a data representation problem: image features are segmented and approximated by a parametric curve or a sequence of model points. However, the use of classic Pattern Recognition methods in bound-ary detection is unusual when compared with more popular approaches, e.g., active

MOORE, WARRELL AND PRINCE: HIERARCHIAL BOUNDARY PRIORS 1 Vistas: Hierarchial boundary priors using multiscale conditional random fields.

by Alastair P. Moore, Jonathan Warrell, Simon J. D. Prince
"... Boundary detection is a fundamental problem in computer vision. However, bound-ary detection is difficult as it involves integrating multiple cues (intensity, color, texture) as well as trying to incorporate object class or scene level descriptions to mitigate the am-biguity of the local signal. In ..."
Abstract - Add to MetaCart
Boundary detection is a fundamental problem in computer vision. However, bound-ary detection is difficult as it involves integrating multiple cues (intensity, color, texture) as well as trying to incorporate object class or scene level descriptions to mitigate the am-biguity of the local signal

Vistas: Hierarchial boundary priors using multiscale conditional random fields.

by Jonathan Warrell, Alastair P. Moore, Simon J. D. Prince
"... Boundary detection is a fundamental problem in computer vision. However, bound-ary detection is difficult as it involves integrating multiple cues (intensity, color, texture) as well as trying to incorporate object class or scene level descriptions to mitigate the am-biguity of the local signal. In ..."
Abstract - Add to MetaCart
Boundary detection is a fundamental problem in computer vision. However, bound-ary detection is difficult as it involves integrating multiple cues (intensity, color, texture) as well as trying to incorporate object class or scene level descriptions to mitigate the am-biguity of the local signal

A ROBUST BAYESIAN MULTISENSOR FUSION ALGORITHM FOR JOINT LANE AND PAVEMENT BOUNDARY DETECTION

by Bing Ma, Sridhar Lakshmanan, Alfred Hero
"... In this paper we propose to simultaneously detect lane and pave-ment boundaries by fusing information from both optical and radar images. The boundaries are described with concentric circular models, whose parameters are compatible and will result in bet-ter conditioned estimation problems than prev ..."
Abstract - Add to MetaCart
Bayesian framework and a joint maximum a posteriori (MAP) estimate is employed to locate the lane and pave-ment boundaries. Experimental results are shown to demonstrate that the fusion algorithm outperforms single sensor based bound-ary detection algorithms in a variety of road scenarios. And it also

Interactive segmentation with intelligent scissors

by Eric N. Mortensen, William A. Barrett - Graphical Models and Image Processing , 1998
"... We present a new, interactive tool called Intelligent Scissors which we use for image seg-mentation. Fully automated segmentation is an unsolved problem, while manual tracing is inaccu-rate and laboriously unacceptable. However, Intelligent Scissors allow objects within digital images to be extracte ..."
Abstract - Cited by 145 (3 self) - Add to MetaCart
in a weighted graph. Optimal graph searching provides mathematically piece-wise optimal bound-aries while greatly reducing sensitivity to local noise or other intervening structures. Robustness is further enhanced with on-the-fly training which causes the boundary to adhere to the specific type of edge

An Investigation of Prosody in Hindi Narrative Speech

by Preethi Jyothi, Jennifer Cole, Mark Hasegawa-johnson, Ana Puri
"... This paper investigates how prosodic elements such as promi-nences and prosodic boundaries in Hindi are perceived. We approach this using data from three sources: (i) native speak-ers of Hindi without any linguistic expertise (ii) a linguisti-cally trained expert in Hindi prosody and finally, (iii) ..."
Abstract - Add to MetaCart
) classi-fiers trained on English for automatic prominence and bound-ary detection. We use speech from a corpus of Hindi narrative speech for our experiments. Our results indicate that non-expert transcribers do not have a consistent notion of prosodic promi-nences. However, they show considerable

K-Farthest-Neighbors-Based Concept Boundary Determination for Support Vector Data Description

by Yanshan Xiao, Bo Liu, Longbing Cao
"... Support vector data description (SVDD) is very useful for one-class classification. However, it incurs high time complexity in handling large scale data. In this paper, we propose a novel and effi-cient method, named K-Farthest-Neighbors-based Concept Bound-ary Detection (KFN-CBD for short), to impr ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Support vector data description (SVDD) is very useful for one-class classification. However, it incurs high time complexity in handling large scale data. In this paper, we propose a novel and effi-cient method, named K-Farthest-Neighbors-based Concept Bound-ary Detection (KFN-CBD for short
Results 1 - 10 of 140