20 citations · 39 across the 6 of their papers we have counts for
9 papers
Accurate smartphone camera simulation using 3D scenes
Zheng Lyu, Thomas Goossens, Brian Wandell +1
We assess the accuracy of a smartphone camera simulation. The simulation is an end-to-end analysis that begins with a physical description of a high dynamic range 3D scene and incl…
Validation of image systems simulation technology using a Cornell Box
Zheng Lyu, Krithin Kripakaran, Max Furth +3
We describe and experimentally validate an end-to-end simulation of a digital camera. The simulation models the spectral radiance of 3D-scenes, formation of the spectral irradiance…
ISETAuto: Detecting vehicles with depth and radiance information
Zhenyi Liu, Joyce Farrell, Brian Wandell
Autonomous driving applications use two types of sensor systems to identify vehicles - depth sensing LiDAR and radiance sensing cameras. We compare the performance (average precisi…
Neural Network Generalization: The impact of camera parameters
Zhenyi Liu, Trisha Lian, Joyce Farrell +1
We quantify the generalization of a convolutional neural network (CNN) trained to identify cars. First, we perform a series of experiments to train the network using one image data…
A convolutional neural network reaches optimal sensitivity for detecting some, but not all, patterns
Fabian H. Reith, Brian A. Wandell
We investigate the performance of modern convolutional neural networks (CNN) and a linear support vector machine (SVM) with respect to spatial contrast sensitivity. Specifically, w…
Soft Prototyping Camera Designs for Car Detection Based on a Convolutional Neural Network
Zhenyi Liu, Trisha Lian, Joyce Farrell +1
Imaging systems are increasingly used as input to convolutional neural networks (CNN) for object detection; we would like to design cameras that are optimized for this purpose. It…