The extent to which member states transpose EU directives in a timely fashion is often argued to be strongly associated with the general effectiveness of national bureaucracies. But what kind of institutional solutions ensure better performance? This paper examines the patterns and effects of departmental oversight across 28 ministries in Estonia, Hungary, Poland and Slovenia. In mapping the strength of oversight, it relies on around 90 structured interviews regarding the rules-in-use on transposition planning, legal review and monitoring of deadlines. The analysis of the impact of departmental oversight is based on an original dataset of over 300 directives with transposition deadlines between January 2005 and December 2008.

On the european union

Thank you very much for reading handbook of image and video processing. As you may know, people have search numerous times for their favorite novels like this handbook of image and video processing, but end up in infectious downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they cope with some harmful bugs inside their laptop. handbook of image and video processing is available in our book collection an online access to it is set as public so you can download it instantly. Our digital library hosts in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the handbook of image and video processing is universally compatible with any devices to read.

Handbook Of Image And Video Processing

Automatic License Plate Recognition via sliding-window darknet-YOLO deep learning

This paper details MORPH a longitudinal face database developed for researchers investigating all facets of adult age-progression, e.g. face modeling, photo-realistic animation, face recognition, etc. This database contributes to several active research areas, most notably face recognition, by providing: the largest set of publicly available longitudinal images; longitudinal spans from a few months to over twenty years; and, the inclusion of key physical parameters that affect aging appearance. The direct contribution of this data corpus for face recognition is highlighted in the evaluation of a standard face recognition algorithm, which illustrates the impact that age-progression, has on recognition rates. Assessment of the efficacy of this algorithm is evaluated against the variables of gender and racial origin. This work further concludes that the problem of age-progression on face recognition (FR) is not unique to the algorithm used in this work.

MORPH: A Longitudinal Image Database of Normal Adult Age-Progression.

A comprehensive survey on impulse and Gaussian denoising filters for digital images

The research considers the implementation of simultaneous localization and mapping algorithm based on the FastSLAM technique and specific problems that are typical for the RGB-D sensor-based solutions. An improvement of the classical FastSLAM algorithm has been obtained by replacing the method of landmarks’ observations filtering with unscented Kalman filters. Instead of linearizing, the nonlinear models through the first order Taylor series expansion at the mean of the landmark state were applied. The proposed algorithm computes a more accurate mean and uncertainty of the landmarks, which are moving nonlinearly. Various data preprocessing issues are discussed, such as the method of calibration of Kinect-like cameras, depth map restoration using a modified interpolation technique, and filtering the noise in the RGB images for more accurate detection of key features. Additionally, the chapter presents an improved resampling algorithm for the particle filtering through the adaptive thresholding based on the data of the effective particle number evolution. The proposed algorithm runs in real time and shows good accuracy and robustness in comparison with other modern SLAM systems using all the advantages and disadvantages of the RGB-D sensors.

Unscented RGB-D SLAM in Indoor Environment

We discuss a method of signal analysis — empirical mode decomposition, and also its modification — complementary ensemble empirical mode decomposition. Both methods are used to research the reconstruction of a speech signal by the means of intrinsic mode functions that were received during the decomposition. Researches were performed using two English databases of speech signals which contain speech sentences. Sentences are pronounced by male and female speakers. We utilized next objective indexes for our investigations: relative power and root mean square error of reconstruction, quality index PESQ and intelligibility index SNRloss. Results of a computational experiment are given. These results demonstrate a high quality of the signal reconstruction at its full restoration, and also advantages of the complementary decomposition in comparison with the customary decomposition.

Research of the speech signal reconstruction at empirical mode decomposition

Neural network algorithms for detecting pathologies on endoscopic images of the stomach have been developed and investigated. The training and testing of the algorithms was carried out on an NVIDIA DGX-I supercomputer using a database of endoscopic images collected in cooperation with the Yaroslavl Oncological Hospital. The mAP metric value was 0.771 for the SSD convolutional neural network algorithm and 0.808 for the RetinaNet algorithm. The test results confirm the feasibility and relevance of the development of decision support systems using artificial intelligence methods in endoscopic practice.

Analysis of Pathologies on Endoscopic Images of the Stomach Using SSD and RetinaNet Neural Network Architecture

An eye center localization algorithm based on multi-block local binary patterns is described Performance of the suggested algorithm is compared to other popular approaches on standard BioID and FERET image databases Additional test on images with two types of distortions: Additive white Gaussian noise and JPEG compression is considered The impact of eye center localization accuracy on face recognition rate is analyzed

Improving the eyes localization algorithm for face recognition systems

A new neuralnetworkadaptive switching median(NASM)filter isproposed toremovesalt-and-pepper impulse noise fromhighly corrupted image. Thealgorithm is developed by combiningadvantages of the known progressive medianfilter withimpulse detection scheme. Neuralnetwork wasincluded intoimpulse detection stepto improve itscharacteristics. Comparison ofthegiven method withtraditional median-type filters isprovided.

Vladimir Khryashchev

Papers

Unscented RGB-D SLAM in Indoor Environment

Research of the speech signal reconstruction at empirical mode decomposition

Analysis of Pathologies on Endoscopic Images of the Stomach Using SSD and RetinaNet Neural Network Architecture

Improving the eyes localization algorithm for face recognition systems

NeuralNetworkAdaptive Switching Median Filter forImage Denoising