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JMLR
2006
132views more  JMLR 2006»
13 years 5 months ago
Learning to Detect and Classify Malicious Executables in the Wild
We describe the use of machine learning and data mining to detect and classify malicious executables as they appear in the wild. We gathered 1,971 benign and 1,651 malicious execu...
Jeremy Z. Kolter, Marcus A. Maloof
MEDIAFORENSICS
2010
13 years 6 months ago
Detecting content adaptive scaling of images for forensic applications
Content-aware resizing methods have recently been developed, among which, seam-carving has achieved the most widespread use. Seam-carving's versatility enables deliberate obj...
Claude Fillion, Gaurav Sharma
MM
2010
ACM
251views Multimedia» more  MM 2010»
13 years 5 months ago
A cognitive approach for effective coding and transmission of 3D video
Reliable delivery of 3D video contents to a wide set of users is expected to be the next big revolution in multimedia applications provided that it is possible to grant a certain ...
Simone Milani, Giancarlo Calvagno
BIODATAMINING
2008
163views more  BIODATAMINING 2008»
13 years 5 months ago
Multivariate profiling of neurodegeneration-associated changes in a subcellular compartment of neurons via image processing
Background: Dysfunction in the endolysosome, a late endosomal to lysosomal degradative intracellular compartment, is an early hallmark of some neurodegenerative diseases, in parti...
Saravana K. Kumarasamy, Yunshi Wang, Vignesh Viswa...
BMCBI
2006
110views more  BMCBI 2006»
13 years 5 months ago
Bias in error estimation when using cross-validation for model selection
Background: Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers...
Sudhir Varma, Richard Simon