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Resources for deep learning with satellite & aerial imagery
This page lists resources for performing deep learning on satellite imagery. To a lesser extent classical Machine learning (e.g. random forests) are also discussed, as are classical image processing techniques. Note there is a huge volume of academic literature published on these topics, and this repository does not seek to index them all but rather list approachable resources with published code that will benefit both the research and developer communities. If you find this work useful...
Yandex.Tank is an extensible open-source load testing tool for advanced Linux users which is especially good as a part of an automated load testing suite. Different load generators are supported. Evgeniy Mamchits' phantom is a very fast (100 000+ RPS) shooter written in C++ (default) JMeter is an extendable and widely known one. BFG is a Python-based generator that allows you to write your load scenarios in Python. Experimental Golang generator: pandora. Performance analytics backend...
This is a game.Player has to save his target point(staff).There is an enemy tank. The enemy tank will be trying to kill the staff.If staff is killed then game will be over. And if player can kill the enemy tank then player will win the game.
Tank Battles is a 3D simulator for teaching robot artificial inteligence. It's
heavilly influenced by Robocode, but differs from the former in that it adds the complexity of a full 3D scene, realistic physics simulation, among other features.