Neslihan EdesComputer Vision, IDEs/ Jupyter, Science
In this talk I want to demonstrate how to leverage existing Open Source technologies to implement basic movement tracking use cases.
Daniel HeinzeComputer Vision, Deep Learning, DevOps, IDEs/ Jupyter, Machine Learning, APIs, Python
Build a Machine Learning pipeline with Jupyter and Azure: https://notebooks.azure.com/Starlord/projects/pycon-ml-jupyter-azure
Harald BoschArtificial Intelligence, Computer Vision, Deep Learning, IDEs/ Jupyter, Machine Learning
Build a ML showcase using #transferlearning, #keras, #WebRTC, #python
Martin ChristenBig Data, Computer Vision, Deep Learning, Data Science, Machine Learning, Visualisation
Detecting Solar Panels from aerial imagery using #Python #DeepLearning #CrowdSourcing
Marysia WinkelsArtificial Intelligence, Algorithms, Computer Vision, Deep Learning, Data Science, Machine Learning, Science
Equivariance in CNNs: how generalising the weight-sharing property increases data-efficiency
Peggy Sylopp, Aislyn RoseArtificial Intelligence, Algorithms, Computer Vision, Deep Learning, Data Science, Machine Learning, Science
Control what you hear with deep learning and open audio databases. The developer and manager of \\NoIze//, a project supported by Prototype Fund, share what’s helped them build an open source smart, low-computational noise filter in Python.
Irina Vidal MigallónArtificial Intelligence, Computer Vision, Deep Learning, Machine Learning
How much time & risk do you have? Ways to robustify your vision NN model before you let it go live.
Nelson MoorenComputer Vision, Science
I built upon Python's OpenCV library to detect locations of dancers in a silent disco, using their headphone lights as a proxy, and performed network analysis to investigate their grouping behaviour based on the playlists people were listening to.