Computer Vision

4 talks from the 2022 edition.

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

Steven Kolawole

Building an E2E working prototype that detects sign language meanings in images/videos and generates equivalent, realistic voice of words communicated by the sign language, in real-time, won't be completed in a day's...
Can you Read This? (Or: how I Improved Text Readability on the Web for the Visually Impaired)

Asya Frumkin

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

Bettina Heinlein

Have you ever been in a situation where you do not know the next step? This talk presents the challenges encountered while building a Computer Vision application, and how problem-solving strategies were utilized....
Grokking LIME: How can we explain why an image classifier "knows" what’s in a photo without looking inside the model?

Kilian Kluge

Many machine learning models are too complex for humans to comprehend. Algorithms like LIME can explain model outputs, even without looking at a model’s internal structure. This talk provides attendees with a deep...