Zobrazeno 1 - 10
of 424
pro vyhledávání: '"A Wandell Brian"'
This paper describes a physics-based end-to-end software simulation for image systems. We use the software to explore sensors designed to enhance performance in high dynamic range (HDR) environments, such as driving through daytime tunnels and under
Externí odkaz:
http://arxiv.org/abs/2408.12048
Autor:
Liu, Zhenyi, Shah, Devesh, Rahimpour, Alireza, Upadhyay, Devesh, Farrell, Joyce, Wandell, Brian A
The design and evaluation of complex systems can benefit from a software simulation - sometimes called a digital twin. The simulation can be used to characterize system performance or to test its performance under conditions that are difficult to mea
Externí odkaz:
http://arxiv.org/abs/2303.00983
Combining image sensor simulation tools (e.g., ISETCam) with physically based ray tracing (e.g., PBRT) offers possibilities for designing and evaluating novel imaging systems as well as for synthesizing physically accurate, labeled images for machine
Externí odkaz:
http://arxiv.org/abs/2202.08880
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 includes a specification of the optics and the image sensor. The simulatio
Externí odkaz:
http://arxiv.org/abs/2201.07411
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 by multi-element optics, and conversion of the irradiance to digital
Externí odkaz:
http://arxiv.org/abs/2105.04106
Autonomous driving applications use two types of sensor systems to identify vehicles - depth sensing LiDAR and radiance sensing cameras. We compare the performance (average precision) of a ResNet for vehicle detection in complex, daytime, driving sce
Externí odkaz:
http://arxiv.org/abs/2101.01843
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 dataset - either synthetic or from a camera - and then test on a different
Externí odkaz:
http://arxiv.org/abs/1912.03604
A convolutional neural network reaches optimal sensitivity for detecting some, but not all, patterns
Autor:
Reith, Fabian H., Wandell, Brian A.
We investigate the performance of modern convolutional neural networks (CNN) and a linear support vector machine (SVM) with respect to spatial contrast sensitivity. Specifically, we compare CNN sensitivity to that of a Bayesian ideal observer (IO) wi
Externí odkaz:
http://arxiv.org/abs/1911.05055
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 is impractical to build different cameras and then acquire and label t
Externí odkaz:
http://arxiv.org/abs/1910.10916
Autor:
Liu, Zhenyi, Shen, Minghao, Zhang, Jiaqi, Liu, Shuangting, Blasinski, Henryk, Lian, Trisha, Wandell, Brian
We describe an open-source simulator that creates sensor irradiance and sensor images of typical automotive scenes in urban settings. The purpose of the system is to support camera design and testing for automotive applications. The user can specify
Externí odkaz:
http://arxiv.org/abs/1902.04258