Instance search is an interesting task as well a challenging issue due to the lack of effective feature representation. In this paper, instance level representation built upon fully convolutional instance-aware segmentation proposed. The ROI-pooled from segmented region. So that instances in various sizes and layouts are represented by deep features uniform length. This further enhanced use def...

Feature models are a de facto standard for representing the commonalities and variability of product lines configurable software systems. Requirements-level features commonly implemented in multiple source code artifacts, resulting complex dependencies at level. As developers add evolve frequently, it is challenging to keep feature consistent with their implementation. This article thus present...

Breast cancer is the most prevalent among women, and diagnosing it early vital for successful treatment. The examination of images captured during biopsies plays an important role in determining whether a patient has or not. However, stochastic patterns, varying intensities colors, large sizes these make challenging to identify mark malignant regions them. Against this backdrop, study proposes ...

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In this paper, we present our experiments in TRECVID 2008 about High-Level feature extraction task. This is the first year for our participation in TRECVID, our system adopts some popular approaches that other workgroups proposed before. We proposed 2 advanced low-level features NEW Gabor texture descriptor and the Compact-SIFT Codeword histogram. Our system applied well-known LIBSVM to train t...

In many real-life usages, single modal biometric systems repeatedly face significant restrictions due to noise in sensed data, spoof attacks, data quality, nonuniversality, and other factors. However, single traits alone may not be able to meet the increasing demand of high accuracy in today’s biometric system.Multibiometric systems is used to increase the performance that may not be possible u...