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Face sketch recognition is one of the recent biometrics, which is used to identify criminals. In this paper, a proposed model is used to identify face sketch images based on local invariant features. In this model, two local invariant feature extraction methods, namely, Scale Invariant Feature Transform (SIFT) and Local Binary Patterns (LBP) are used to extract local features from photos and sketches...
This paper presents a novel method for combining the outputs of different gender classification techniques based on facial images. Merging the methods is performed by a committee machine using the Bayesian theorem. We implement and compare several well-known individual classifiers on four different datasets, then we experiment the proposed machine, and show that it significantly improves the accuracy...
In mobile IPv6, packet transfer is interrupted due to the handoff of a mobile node, which results in burst packet loss. This transient behavior decreases the required quality of services for time-critical streaming media applications. This paper introduces an analytical model of streamed video over mobile IP networks considering the effects of handoff. The proposed model focuses on the effect of the...
Lung nodules from low dose CT (LDCT) scans may be used for early detection of lung cancer. However, these nodules vary in size, shape, texture, location, and may suffer from occlusion within the tissue. This paper presents an approach for segmentation of lung nodules detected by a prior step. First, regions around the detected nodules are segmented; using automatic seed point placement levels sets...
Mobile IP has been developed to provide the continuous information network access to mobile users. The performance of Mobile IP mobility management scheme is dependent on traffic characteristics and user mobility. Consequently, it is important to assess this performance in-depth through these factors. This paper introduces a novel analytical model of handoff management in mobile IP networks. The proposed...
In this paper, we document the face detection competition that we have organized in conjunction with the ISDA 2010 conference. The objective was to compare different face detection engines performance on new unpublished datasets. We believe researchers can benefit from this competition by identifying strong and weak areas in their algorithms relative to others. We have also identified, based on the...
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