Source Code

The code for the following papers is available:

• Cross-domain challenge for panoptic segmentation in agriculture with the related code.

• Panoptic One-Click Segmentation: here is where you can access the paper and the related code.

• End-to-end panoptic 3D representations or PAg-NeRF has the code and paper available here. You can also view a video of the results with a brief explanation.

• The paper and code for Spatial-Temporal DNNs, which won Best AgRobotics Paper at IROS'22) is available here. 

• Code for mixtures of deep convolutional neural networks (MixDCNN) is available on github here.

• "A Scalable Formulation of Probabilistic Linear Discriminant Analysis: Applied to Face Recognition" has been published in IEEE TPAMI and "Session Variability Modelling for Face Authentication"  which provides details on how to implement ISV and JFA has been published in IET Biometrics. Implementations for both of these are available in bob.

• The Bob project, is something that I helped contribute to. It contains code for machine learning and computer vision. Several of the techniques that I have published about have been implemented here including probabilistic linear discriminant analysis, joint factor analysis and Gaussian mixture models. It is written in C++ for efficiency but has many Python wrappers to allow for rapid development, you can also seamlessly use scipy/numpy functionality as well.