Neural Attention-Driven Non-Maximum Suppression for Person Detection.

Non-maximum suppression (NMS) is a post-processing step in almost every visual object detector. NMS aims to prune the number of overlapping detected candidate regions-of-interest (RoIs) on an image, in order to assign a single and spatially accurate detection to each object. The default NMS algorithm (GreedyNMS) is fairly simple and suffers from severe drawbacks, due to its need for manual tuning.

Multimodal Stereoscopic Movie Summarization Conforming to Narrative Characteristics.

Video summarization is a timely and rapidly developing research field with broad commercial interest, due to the increasing availability of massive video data. Relevant algorithms face the challenge of needing to achieve a careful balance between summary compactness, enjoyability, and content coverage. The specific case of stereoscopic 3D theatrical films has become more important over the past years, but not received corresponding research attention.

Reproductive and obstetric outcome after laparoscopic excision of functional, non-communicating broadly attached rudimentary horn: a case series.

Objective: To present the reproductive and obstetric outcome after laparoscopic excision of functional, non-communicating broadly attached rudimentary horn.

Study Design: As a part of a retrospective study performed over the past 21 years to determine the reproductive and obstetric outcome after laparoscopic treatment for symptomatic non-communicating rudimentary horn, we identified seven women who became pregnant after laparoscopic removal of the broadly attached rudimentary horn. The main outcome measures were reproductive outcome, preterm birth, mode of delivery, birth weight, pregnancy-induced hypertension, antenatal bleeding and presence of other congenital anomalies.

Nonnegative matrix factorization in polynomial feature space.

Plenty of methods have been proposed in order to discover latent variables (features) in data sets. Such approaches include the principal component analysis (PCA), independent component analysis (ICA), factor analysis (FA), etc., to mention only a few.

An optimal detector structure for the fourier descriptors domain watermarking of 2D vector graphics.

Abstract-Polygonal lines constitute a key graphical primitive in 2D vector graphics data. Thus, the ability to apply a digital watermark to such an entity would enable the watermarking of cartoons, drawings, and Geographical Information Systems (GIS) data in vector graphics format. This paper builds on and extends an existing algorithm that achieves polygonal line watermarking by modifying the Fourier descriptors magnitude in an imperceptible way.

Digital image processing techniques for the detection and removal of cracks in digitized paintings.

An integrated methodology for the detection and removal of cracks on digitized paintings is presented in this paper. The cracks are detected by thresholding the output of the morphological top-hat transform. Afterward, the thin dark brush strokes which have been misidentified as cracks are removed using either a median radial basis function neural network on hue and saturation data or a semi-automatic procedure based on region growing.