Unsupervised Domain Adaptation (UDA) is a powerful strategy for bridging the gap between synthetic (source) data and real-world (target) data, thereby reducing expensive manual annotations. In this ...

Medical image repositories have been rapidly growing due to the widespread use of imaging techniques, making manual annotation unfeasible. Efficient image retrieval systems are crucial for diagnosing ...

Traditional approaches to autonomous vehicles (AVs) rely on using millions of miles of driving data in conjunction with even more miles of simulated data as inputs to supervised machine learning ...

Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...