PyData: Computer Vision | PyConDE & PyData Berlin 2022

Talk pydata-computer-vision

Building a Sign-to-Speech prototype with TensorFlow, Pytorch and DeepStack: How it happened & What I learned

Steven Kolawole

Computer Vision, Neural Networks / Deep Learning

Building an E2E working prototype that detects sign language meanings in images/videos and generate equivalent voice of words communicated by the sign language, in real-time, won't be completed in a day's work. Here I'd explain how it happened and what I learned in the process.

Talk pydata-computer-vision

Can you Read This? (Or: how I Improved Text Readability on the Web for the Visually Impaired)

Asya Frumkin

Algorithms, Computer Vision, Neural Networks / Deep Learning

I will explain my approach of detecting texts on top of an image background that are unreadable to people with visual impairment. I will explain the challenges I. encountered when using different OCR architectures for this task and talk about the solution I came up with.

Talk pydata-computer-vision

Challenge Accepted - How to Escape the Quicksand While Engineering a Computer Vision Application

Bettina Heinlein

Computer Vision

Leveraging problem-solving strategies for challenges in building Computer Vision applications and beyond, illustrated with a recent Computer Vision project.

Talk pydata-computer-vision

Grokking LIME: How can we explain why an image classifier "knows" what’s in a photo without looking inside the model?

Kilian Kluge

Computer Vision, Neural Networks / Deep Learning, Transparency / Interpretability

How can LIME explain machine-learning models without peeking inside? Let's find out!