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A deep CNN-based framework for enhanced aerial imagery registration with applications to UAV geolocalization

In this paper we present a novel framework for geolocalizing Unmanned Aerial Vehicles (UAVs) using only their onboard camera. The framework exploits the abundance of satellite imagery, along with established computer vision and deep learning methods, to locate the UAV in a satellite imagery map. It utilizes the contextual information extracted from the scene to attain increased geolocalization

Artificial Intelligence
Software and Communications

Hybrid Information Filtering Engine for Personalized Job Recommender System

The recommendation system, also known as recommender system or recommendation engine/platform, is considered as an interdisciplinary field. It uses the techniques of more than one field. Recommender system inherits approaches from all of machine learning, data mining, information retrieval, information filtering and human-computer interaction. In this paper, we propose our value-added architecture

Artificial Intelligence

Gesture recognition for improved user experience in augmented biology lab

The Learning process in education systems is one of the most important issues that affect all societies. Advances in technology have influenced how people communicate and learn. Gaming Techniques (GT) and Augmented Reality (AR) technologies provide new opportunities for a learning process. They transform the student’s role from passive to active in the learning process. It can provide a realistic

Artificial Intelligence
Healthcare

HTTP application layer DDoS attack mitigation using resources monitor

Denial of Service attacks are one of the most annoying day to day challenges for any security expert and IT professional. This is according to the attack nature. It can be run against any kind of network resources, whether exposed to the Internet or internally in a corporate network, regardless of the type of service it provides and its role in the network. There is no one complete solution or

A postmortem forensic analysis for a JavaScript based attack

[No abstract available]

Vision capabilities for a humanoid robot tutoring biology

Robots are expected to be the future solution in various fields. One of these fields is education. Teachers, students and robots have to work together to make this assumption true. For this, robots must have the adequate capabilities that can help them succeed. Vision of the robot is an essential tool that the robot uses to perform several tasks. Hence, it has to be taken into consideration, the

Artificial Intelligence

Optical character recognition using deep recurrent attention model

We address the problem of recognizing multi-digit numbers in optical character images. Classical approaches to solve this problem include separate localization, segmentation and recognition steps. In this paper, an integrated approach to multi-digit recognition from raw pixels to ultimate multi class labeling is proposed by using recurrent attention model based on a spatial transformer model

Artificial Intelligence

Innovative human-robot interaction for a robot tutor in biology game

Robots nowadays, are introduced to many domains and fields. One of these fields is education. We introduce integrating robots and games in education. We have designed a humanoid robot tutoring biology. Our robot is interacting with a student to play a game to enhance and examine the student's knowledge. In our game, we developed cognitive capabilities for the robot. We analyzed the features that

Circuit Theory and Applications
Software and Communications
Mechanical Design
Innovation, Entrepreneurship and Competitiveness

Experimental digital forensics of subscriber identification module (SIM) Card

[No abstract available]

Software and Communications

Convolutional Neural Network-Based Deep Urban Signatures with Application to Drone Localization

Most commercial Small Unmanned Aerial Vehicles (SUAVs) rely solely on Global Navigation Satellite Systems (GNSSs) - such as GPS and GLONASS - to perform localization tasks during the execution of autonomous navigation activities. Despite being fast and accurate, satellite-based navigation systems have typical vulnerabilities and pitfalls in urban settings that may prevent successful drone

Artificial Intelligence
Software and Communications