For Muslims in the United States, there is no other time more centered around gathering in congregation than the holy month of Ramadan. In every corner of the country, believers attend community iftar meals to break the fast and then pack neatly into tight rows for nightly prayers at the mosque. On weekends, especially, some may linger longer as they catch up, share in the pre-dawn suhoor meal and line up again for the fajr, dawn, prayers.
There are no public statistics available for how many Saudi women try to flee abroad each year. The most recent statistics from the Ministry of Labor and Social Development show that 577 Saudi women tried to flee their homes within Saudi Arabia in 2015. That figure is likely to be much higher in reality because many families do not report runaways for fear of social stigma.
Unity Technologies has a new game that you can't play. The maker of game development tools is releasing a new title called Obstacle Tower that is designed to challenge the capabilities of artificial intelligence. The release of the title is being accompanied by a contest, the Obstacle Tower Challenge, that will allow participants to run their AI agents through the 100-level challenge and compete for prizes. According to Unity, Obstacle Tower provides a game-like environment for machine learning researchers to play around with and fine-tune their AI. The tower operates similarly to a standard platforming game.
"We talk about the three-peat because it's in front of us. We don't repeat it every single day," he said. "When we start the season, we lay everything out onto the table as to what's at stake as far as expectations. Yes, winning a championship is the goal. How you get there, how you break up that mission on a game-to-game, month-to-month basis is what makes us great.
Advances in Unmanned Aerial Vehicles (UAVs), also known as drones, offer unprecedented opportunities to boost a wide array of large-scale Internet of Things (IoT) applications. Nevertheless, UAV platforms still face important limitations mainly related to autonomy and weight that impact their remote sensing capabilities when capturing and processing the data required for developing autonomous and robust real-time obstacle detection and avoidance systems. In this regard, Deep Learning (DL) techniques have arisen as a promising alternative for improving real-time obstacle detection and collision avoidance for highly autonomous UAVs. This article reviews the most recent developments on DL Unmanned Aerial Systems (UASs) and provides a detailed explanation on the main DL techniques. Moreover, the latest DL-UAV communication architectures are studied and their most common hardware is analyzed.