Roadmap

Robotics Academy - Improve Deep learning Exercise

Goals

*Custom train or find an enhanced DL model trained to detect only humans specifically. Changes to the pre-processing and post-processing part would have to be made as per the input and output structure of the new model. *Enhancing the model benchmarking part in terms of its interpretability, use case, accuracy, and visual appeal to the user. *Enabling GPU support while executing the exercise from the docker container. *Fluent exercise execution. *Building a tutorial for the exercise using the Keras Framework, which uses Theano and Tensorflow frameworks as backend.

References

[1] https://github.com/JdeRobot/RoboticsAcademy
[2] https://github.com/JdeRobot/DeepLearningStudio
[3] https://developer.nvidia.com/tensorrt
[4] https://www.tensorflow.org/api_docs/python/tf/quantization/quantize
[5] https://www.tensorflow.org/model_optimization/guide/pruning
[6] MobileNetV2: Inverted Residuals and Linear Bottlenecks.” 2018 https://arxiv.org/abs/1801.04381
[7] Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding https://arxiv.org/abs/1510.00149
[8] Knowledge Distillation https://intellabs.github.io/distiller/knowledge_distillation.html