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» Intrusion detection techniques and approaches
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TMI
2010
172views more  TMI 2010»
13 years 9 months ago
Comparison of AdaBoost and Support Vector Machines for Detecting Alzheimer's Disease Through Automated Hippocampal Segmentation
Abstract— We compared four automated methods for hippocampal segmentation using different machine learning algorithms (1) hierarchical AdaBoost, (2) Support Vector Machines (SVM)...
Jonathan H. Morra, Zhuowen Tu, Liana G. Apostolova...
CVPR
2008
IEEE
15 years 25 days ago
Object tracking and detection after occlusion via numerical hybrid local and global mode-seeking
Given an object model and a black-box measure of similarity between the model and candidate targets, we consider visual object tracking as a numerical optimization problem. During...
Zhaozheng Yin, Robert T. Collins
ICCD
2006
IEEE
97views Hardware» more  ICCD 2006»
14 years 7 months ago
Pesticide: Using SMT Processors to Improve Performance of Pointer Bug Detection
Pointer bugs associated with dynamically-allocated objects resulting in out-of-bounds memory access are an important class of software bugs. Because such bugs cannot be detected e...
Jin-Yi Wang, Yen-Shiang Shue, T. N. Vijaykumar, Sa...
MSR
2006
ACM
14 years 4 months ago
Detecting similar Java classes using tree algorithms
Similarity analysis of source code is helpful during development to provide, for instance, better support for code reuse. Consider a development environment that analyzes code whi...
Tobias Sager, Abraham Bernstein, Martin Pinzger, C...
KBSE
2005
IEEE
14 years 4 months ago
Optimized run-time race detection and atomicity checking using partial discovered types
Concurrent programs are notorious for containing errors that are difficult to reproduce and diagnose. Two common kinds of concurrency errors are data races and atomicity violation...
Rahul Agarwal, Amit Sasturkar, Liqiang Wang, Scott...