Deep reinforcement learning (DRL) has shown incredible performance in learning various tasks to the human level. However, unlike human perception, current DRL models connect the entire low-level sensory input to the state-action values rather than exploiting the relationship between and among entities that constitute the sensory input. Because of this difference, DRL needs vast amount of experi...

In this paper, we proposed a new method for spatially registered multi-focus images fusion. Image fusion based on wavelet transform is the most commonly fusion method, which fuses the source images information in wavelet domain according to some fusion rules. There are some disadvantages in Discrete Wavelet Transform, such as shift variance and poor directionality. Also, because of the uncertai...

Requirements engineering education should be based on best-practices and techniques, but it also needs to be anchored in state of the art research and the reality of industry practice. Preparing students for practice involves giving them an accurate view of reality as well as giving them the tools and the critical mindset needed to perform and improve on requirements engineering practices in in...

This paper presents a method for removing focal blur in images using fusion algorithm. Different focal images can be combined to give a single fused image with all focused information. Pattern selective image fusion provides a mechanism for combining multiple images through identifying salient features in the source images and combining those features in to a single fused image. However one of ...

Natural language interfaces to data services will be a key technology to guarantee access to huge data repositories in an effortless way. This involves solving the complex problem of recognizing a relevant service or service composition given an ambiguous, potentially ungrammatical natural language question. As a first step toward this goal, we study methods for identifying the salient terms (o...

In digital photography, two or more objects of a scene cannot be focused at the same time. If we focus one object, we may lose information about other objects and vice versa. Multi-focus image fusion is a process of generating an all-in-focus image from several out-of-focus images. In this paper, we propose a new multi-focus image fusion method based on two-scale image decomposition and salienc...

Optics of lenses with a high degree of magnification suffers from the problem of a limited depth of field. As the focal length and magnification of the lens increase, the depth of field decreases. As a result, it is often not possible to get an image that contains all relevant objects in focus. To overcome the problem of finite depth of field, image fusion technique is designed which combines t...

Im Beitrag wird ein ganzheitliches Visualisierungsund Interaktionskonzept für die Überwachung und Diagnose eines großen Straßennetzes sowie die Manipulation von Prozessvariablen im Kontext einer Verkehrsleitzentrale vorgestellt. Um das kooperative Arbeiten zu unterstützen wird das Konzept einer Multi-Focus-View in Kombination mit einer inhaltssensitiven Navigation verfolgt. Ziel ist es, die Nav...

We introduce in this paper a region based multi-focus image fusion algorithm using spatial frequency and genetic algorithm. The basic idea is to divide the source images into blocks, and then select the corresponding blocks with higher spatial frequency value to construct the resultant fused image. GA is brought forward to determine the suitable sizes of the block.

The main objective is to bring up a highly informative image as result using image fusion. In this paper, A unique method for image fusion using sparse representation is used. The sparse coefficients are used as image features. The source image could be identified with common features and innovative features. The use of sparse representation for the extraction of common and innovative features,...