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

An application for video data analysis based on computer vision methods is presented. The proposed system consists of five consecutive stages: face detection, face tracking, gender recognition, age classification and statistics analysis. AdaBoost classifier is utilized for face detection. A modification of Lucas and Kanade algorithm is introduced on the stage of tracking. Novel gender and age classifiers based on adaptive features and support vector machines are proposed. All the stages are united into a single system of audience analysis. The proposed software complex can find its applications in different areas, from digital signage and video surveillance to automatic systems of accident prevention and intelligent human-computer interfaces.

/pdf/application-for-video-analysis-based-on-machine-learning-and-2xul7vbws6.pdf

Application for video analysis based on machine learning and computer vision algorithms

Results of training of convolutional neural network for satellite four-channel image segmentation are performed. Input images contain blue, green, red and near-infrared channels. The algorithm was trained to detect buildings and other urban areas. Modification of the U-Net neural network with two encoders was used. The values of Sorensen coefficient and Jaccard index were calculated for 16 different urban regions.

Modification of U-Net neural network in the task of multichannel satellite images segmentation

A new neural network adaptive switching median (NASM) filter is proposed to remove salt-and-pepper impulse noise from highly corrupted image The algorithm is developed by combining advantages of the known progressive median filter with impulse detection scheme Neural network was included into impulse detection step to improve its characteristics Comparison of the given method with traditional median-type filters is provided

Neural Network Adaptive Switching Median Filter for Image Denoising

A new neural network adaptive switching median (NASM) filter is proposed to remove salt-and-pepper impulse noise from corrupted image. The algorithm is developed by combining advantages of the known median-type filters with impulse detection scheme and the neural network was included into impulse detection step to improve its characteristics. Comparison of the given method with traditional filters is provided. A visual example is given to demonstrate the performance of the proposed filter.

Neural network adaptive switching median filter for the restoration of impulse noise corrupted images

Computer-aided diagnosis of cancer based on endoscopic image analysis is a promising area in the field of computer vision and machine learning. Convolutional neural networks are one of the most popular approaches in endoscopic image analysis. This paper presents the algorithm of pathology detection in endoscopic images of gastric lesions based on convolutional neural network. Training and testing of the algorithm was carried out on the NVIDIA DGX-1 supercomputer using endoscopic images from the test base, assembled together with the Yaroslavl Regional Cancer Hospital. As a result of experiments, the mAP metric was calculated and the value was 0.875, which is a high result for the task of object detection in images.

Vladimir Khryashchev

Papers

Application for video analysis based on machine learning and computer vision algorithms

Modification of U-Net neural network in the task of multichannel satellite images segmentation

Neural Network Adaptive Switching Median Filter for Image Denoising

Neural network adaptive switching median filter for the restoration of impulse noise corrupted images

Deep Learning for Gastric Pathology Detection in Endoscopic Images