This research is devoted to the investigation of issues concerning widespread integration into business communities in order achieve common goals. result society’s evolving requirements, which need a sustainable solution 21st century. Organizations alone cannot create advanced solutions modern times, so legally independent “equal” participants band together solve goals improve overall competiti...

This paper presents a log-polar image representation composed of low-level features extracted using a connectionist approach. The low level features (edges, bars, blobs and ends) are based on Marr's primal sketch hypothesis for the human visual system 3] and are used as the entry point of an iconic vision system 1]. This unusual image representation has been created using a neural network that ...

This study presents a method to reconstruct a high-resolution image using a deep convolution neural network. We propose a deep model, entitled Deep Block Super Resolution (DBSR), by fusing the output features of a deep convolutional network and a shallow convolutional network. In this way, our model benefits from high frequency and low frequency features extracted from deep and shallow networks...

Development and usage of online social networking web sites are growing rapidly. Millions members of these web sites publicly articulate mutual "friendship" relations and share user-created contents, such as photos, videos, files, and blogs. The advances in web designing technology and fast growing usage of online resources prompted web designers to improve features and architectures of social ...

background: co-authorship is one of the most tangible forms of research collaboration. a co-authorship network is a social network in which the authors through participation in one or more publication through an indirect path have linked to each other. the present research using the social network analysis studied co-authorship network of 681 articles published in journal of research in medical...

The dominant paradigm for video-based action segmentation is composed of two steps: first, for each frame, compute low-level features using Dense Trajectories or a Convolutional Neural Network that encode spatiotemporal information locally, and second, input these features into a classifier that captures high-level temporal relationships, such as a Recurrent Neural Network (RNN). While often ef...

This paper introduces a novel mobile robot architecture based on a Situated Belief Network, a belief network that is dynamically updated as a consequence of its current environment. We initially show that it is possible to employ connectionist mechanisms to learn high-level features of the environment from the low-level (sonar) inputs of the robot. These high-level features can then be reasoned...