Learn More
Content based image retrieval (CBIR) has become one of the most active research areas in the past few years. Many indexing techniques are based on global feature distributions. However, these global distributions have limited discriminating power because they are unable to capture local image information. In this paper, we propose a content-based image(More)
Pattern recognition and machine learning techniques have been increasingly adopted in adversarial settings such as spam, intrusion, and malware detection, although their security against well-crafted attacks that aim to evade detection by manipulating data at test time has not yet been thoroughly assessed. While previous work has been mainly focused on(More)
—A new dynamic classifier fusion method named L-GEM Fusion Method (LFM) for Multiple Classifier Systems (MCSs) is proposed. The localized generalization error upper bound for the neighborhood of a testing sample is calculated and used to estimate the local competence of base classifiers in MCSs. Different from the recent dynamic classifier selection(More)