The problem of logo recognition is of great interest in the document domain, especially for databases, because of its potential for identifying the source of the document and its generality as a recognition problem. By recognizing the logo we obtain semantic information about the document, which may be useful in deciding whether or not to analyze the textual components. In this paper, we presen...

Logo localization and recognition is difficult in natural images due to perspective deformations, varying background, possible occlusions, scaling variability; furthermore, the re–branding induces changes in the logo color palette and spatial distribution. To address this task, we locate keypoints using Affine Difference of Gaussian described by SIFT elliptical features; we construct the class ...

SUMMARY LogoBar is a Java application to display protein sequence logos. In our software gaps are accounted for when calculating the information content present at each residue position in a multiple alignment. The resulting logo is displayed as a graph consisting of bars, although traditional letter representation is also possible. Amino acids are displayed from the bottom up with decreasing f...

Spacer oligonucleotide (spoligotyping) analysis is a rapid polymerase chain reaction-based method of DNA fingerprinting the Mycobacterium tuberculosis complex. We examined spoligotype data using a bioinformatic tool (sequence logo analysis) to elucidate undisclosed phylogenetic relationships and gain insights into the global dissemination of strains of tuberculosis. Logo analysis of spoligotypi...

SUMMARY Two Sample Logo is a web-based tool that detects and displays statistically significant differences in position-specific symbol compositions between two sets of multiple sequence alignments. In a typical scenario, two groups of aligned sequences will share a common motif but will differ in their functional annotation. The inclusion of the background alignment provides an appropriate und...

In recent years, top referred methods on object detection like R-CNN have implemented this task as a combination of proposal region generation and supervised classification the proposed bounding boxes. Although pipeline has achieved state-of-the-art results in multiple datasets, it inherent limitations that make very complex inefficient computational terms. Instead considering standard strategy...