4 papers
Depth Estimation using Weighted-loss and Transfer Learning
Muhammad Adeel Hafeez, Michael G. Madden, Ganesh Sistu +1
Depth estimation from 2D images is a common computer vision task that has applications in many fields including autonomous vehicles, scene understanding and robotics. The accuracy…
Beyond the Known: Adversarial Autoencoders in Novelty Detection
Muhammad Asad, Ihsan Ullah, Ganesh Sistu +1
In novelty detection, the goal is to decide if a new data point should be categorized as an inlier or an outlier, given a training dataset that primarily captures the inlier distri…
Synthesizing CTA Image Data for Type-B Aortic Dissection using Stable Diffusion Models
Ayman Abaid, Muhammad Ali Farooq, Niamh Hynes +2
Stable Diffusion (SD) has gained a lot of attention in recent years in the field of Generative AI thus helping in synthesizing medical imaging data with distinct features. The aim…
NeurIPS'22 Cross-Domain MetaDL competition: Design and baseline results
Dustin Carrión-Ojeda, Hong Chen, Adrian El Baz +6
We present the design and baseline results for a new challenge in the ChaLearn meta-learning series, accepted at NeurIPS'22, focusing on "cross-domain" meta-learning. Meta-learning…