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Found 7 papers, 1 papers with code
STEREOFOG -- Computational DeFogging via Image-to-Image Translation on a real-world Dataset
Image-to-Image translation (I2I) is a subtype of Machine Learning (ML) that has tremendous potential in applications where two domains of images and the need for translation between the two exist, such as the removal of fog.
Machine Learning enables Ultra-Compact Integrated Photonics through Silicon-Nanopattern Digital Metamaterials
In this work, we demonstrate three ultra-compact integrated-photonics devices, which are designed via a machine-learning algorithm coupled with finite-difference time-domain (FDTD) modeling.
A needle-based deep-neural-network camera
We experimentally demonstrate a camera whose primary optic is a cannula (diameter=0. 22mm and length=12. 5mm) that acts a lightpipe transporting light intensity from an object plane (35cm away) to its opposite end.
Classification of optics-free images with deep neural networks
The thinnest possible camera is achieved by removing all optics, leaving only the image sensor.
Learning Wavefront Coding for Extended Depth of Field Imaging
Depth of field is an important factor of imaging systems that highly affects the quality of the acquired spatial information.
Lensless-camera based machine learning for image classification
Machine learning (ML) has been widely applied to image classification.
Lensless Photography with only an image sensor
These space-variant point-spread functions are combined with a reconstruction algorithm in order to image simple objects displayed on a discrete LED array as well as on an LCD screen.
