We design and analyze two new low depth algorithms for amplitude estimation (AE) achieving an optimal tradeoff between the quantum speedup circuit depth. For β∈(0,1]...

Distance estimation is a challenge for robots, human beings, and other animals in their adaptation to changing environments. Different approaches have been proposed tackle this problem based on classical vision algorithms or, more recently, deep learning. We present novel approach inspired by mechanisms involved fixational movements estimate depth image with monocular camera. An algorithm micro...

In monocular depth estimation, disturbances in the image context, like moving objects or reflecting materials, can easily lead to erroneous predictions. For that reason, uncertainty estimates for each pixel are necessary, particular safety-critical applications such as automated driving. We propose a post hoc estimation approach an already trained and thus fixed model, represented by deep neura...