The variation of the instantaneous power versus distance for a narrowband channel is an important parameter in modern digital systems, relevant for variations during a burst and for power control algorithms. This paper gives the statistical distribution for the power gradient, both in decibels and in natural units for a Rayleigh fading channel. The former has been known for some time to be Stud...

We propose a meta-learning approach for learning gradient-based reinforcement learning (RL) algorithms. The idea is to evolve a differentiable loss function, such that an agent, which optimizes its policy to minimize this loss, will achieve high rewards. The loss is parametrized via temporal convolutions over the agent’s experience. Because this loss is highly flexible in its ability to take in...

There are social gradients in general and oral health. Few studies have examined the pathways towards the gradients in oral health and compared them to the pathways suggested for general health gradients. The objectives of this thesis are: (1) to examine and compare the social gradients in selected indicators of oral and general health, (2) to examine the gradients in selected indicators of hea...

This paper proposes a multiple exposure images based traffic light recognition method. For traffic light recognition, color segmentation is widely used to detect traffic light signals; however, the color in an image is easily affected by various illuminations and leads to incorrect recognition results. In order to overcome the problem, we propose the multiple exposure technique which enhances t...

In this paper we improve the histogram of oriented gradients (HOG), a core descriptor of state-of-the-art object detection, by the use of higher-level information coming from image segmentation. The idea is to re-weight the descriptor while computing it without increasing its size. The benefits of the proposal are two-fold: (i) to improve the performance of the detector by enriching the descrip...

In principle, the orange skin surface defect can be successfully detected with the use of a set of relatively simple image processing techniques. To assess the technical possibilities of classifying relatively small surfaces the Histogram of Oriented Gradients (HOG) and the Support Vector Machine were used for two sets of about 400 surface patches in each. Color, grey and binarized images were ...

We have developed a method for the detection of both generic flight neighbouring aircrafts and those on a collision course. Our approach employs a sliding window linear Support Vector Machine (SVM) classifier with a Histogram of Oriented Gradients (HOG) feature representation. An extension of this approach to the spatio-temporal domain is also considered and we demonstrate its advantage for the...

Gradient-based descriptors have proven successful in a wide variety of applications. Their standard implementations usually assume that the input images have been acquired using classic perspective cameras. In practice many real-world systems make use of wide angle cameras which allow to obtain wider Fields of View (FOV) but introduce radial distortion which breaks the rectilinear assumption. T...

The objective of this paper is to propose a combinatorial encoding method based on VLAD to facilitate the promotion of accuracy for large scale image retrieval. Unlike using a single feature in VLAD, the proposed method applies multiple heterogeneous types of features, such as SIFT, SURF, DAISY, and HOG, to form an integrated encoding vector for an image representation. The experimental results...

Surveillance based on Computer Vision has become a major necessity in current era. Most of the surveillance systems operate on visible light imaging, but performance based on visible light imaging is limited due to some factors like variation in light intensity during the daytime. The matter of concern lies in the need for processing images in low light, such as in the need of nighttime surveil...