Out-of-Distribution (OOD) detection, the task of identifying inputs that a model has not been trained on, is fundamental for the safe and reliable deployment of deep learning models in real-world applications like autonomous driving and healthcare. Models that perform well on familiar, in-distribution...
Semantic Segmentation, the task of assigning a class label to every pixel in an image, is fundamental for detailed scene understanding, especially in applications like autonomous driving and robotics. However, creating these pixel-perfect annotations is laborious. Furthermore, real-world systems often need to learn...
In this research, we attempt to understand the neural model architecture by computing an importance score to neurons. The computed importance score can be used to prune the model or to understand which features are more meaningful to the trained ANN (artificial neural...
During my work at Microsoft Research Lab in Cairo, we were brainstorming for research projects related to our work Skype Translator for the upcoming summer internship.I got the idea of making a machine translation system that keeps the lost gender information while translating from Arabic To English.
During my work at Microsoft Research Lab in Cairo , my first task was to make a Levantine Arabic dialect to English NMT system, but the parallel data available for dialectical Levantine was not enough to train a decent model for Skype translator.