Search Results for "ndoc-enhanced"

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...

...With Unity Machine Learning Agents (ML-Agents), you are no longer “coding” emergent behaviors, but rather teaching intelligent agents to “learn” through a combination of deep reinforcement learning and imitation learning. Using ML-Agents allows developers to create more compelling gameplay and an enhanced game experience. Advancement of artificial intelligence (AI) research depends on figuring out tough problems in existing environments using current benchmarks for training AI models. Using Unity and the ML-Agents toolkit, you can create AI environments that are physically, visually, and cognitively rich.

...The repository includes MATLAB-based training and testing scripts, along with pre-trained models and pre-computed region proposals for reproducibility. Multiple testing configurations are available, including multi-frame input and enhanced versions that refine tracking boxes and integrate detection confidence across frames.