Results 31 to 40 of about 9,181,016 (294)

Learning Wavefront Coding for Extended Depth of Field Imaging [PDF]

, 2020
Depth of field is an important factor of imaging systems that highly affects the quality of the acquired spatial information. Extended depth of field (EDoF) imaging is a challenging ill-posed problem and has been extensively addressed in the literature ...
Akpinar, Ugur, Gotchev, Atanas, Meem, Monjurul, Menon, Rajesh, Sahin, Erdem   +4 more
core   +2 more sources

Smart computational light microscopes (SCLMs) of smart computational imaging laboratory (SCILab)

PhotoniX, 2021
Computational microscopy, as a subfield of computational imaging, combines optical manipulation and image algorithmic reconstruction to recover multi-dimensional microscopic images or information of micro-objects. In recent years, the revolution in light-
Yao Fan, Jiaji Li, Linpeng Lu, Jiasong Sun, Yan Hu, Jialin Zhang, Zhuoshi Li, Qian Shen, Bowen Wang, Runnan Zhang, Qian Chen, Chao Zuo   +11 more
semanticscholar   +2 more sources

Multimodal Attention-Aware Convolutional Neural Networks for Classification of Hyperspectral and LiDAR Data

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
The attention mechanism is one of the most influential ideas in the deep learning community, which has shown excellent efficiency in various computer vision tasks.
Haotian Zhang, Jing Yao, Li Ni, Lianru Gao, Min Huang   +4 more
doaj   +1 more source

Computational Imaging

The Review of Laser Engineering, 2022
AbstractSince the advent of smartphones, photography is increasingly being done with small, portable, multi-function devices. Relative to the purpose-built cameras that dominated previous eras, smartphone cameras must overcome challenges related to their small form factor.
openaire   +2 more sources

Vehicle Detection Based on Adaptive Multimodal Feature Fusion and Cross-Modal Vehicle Index Using RGB-T Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
Target detection is a critical task in interpreting aerial images. Small target detection, such as vehicles, is challenging. Different lighting conditions affect the accuracy of vehicle detection.
Yuanfeng Wu, Xinran Guan, Boya Zhao, Li Ni, Min Huang   +4 more
doaj   +1 more source

Quantum-inspired computational imaging [PDF]

, 2018
Computational imaging combines measurement and computational methods with the aim of forming images even when the measurement conditions are weak, few in number, or highly indirect.
Altmann, Yoann, Faccio, Daniele, Goyal, Vivek K., Hero, Alfred O., McLaughlin, Stephen, Padgett, Miles J.   +5 more
core   +2 more sources

A perturbation approach for ultrafast calculation of RF field enhancements near medical implants in MRI

Scientific Reports, 2022
Patients with medical implants often are deprived of magnetic resonance imaging examination because of safety risks. One specific risk is the enhancement of the radiofrequency fields around the medical implant potentially resulting in significant tissue ...
Peter R. S. Stijnman, Bart R. Steensma, Cornelis A. T. van den Berg, Alexander J. E. Raaijmakers   +3 more
doaj   +1 more source

Scientific Computational Imaging Code (SCICO)

Journal of Open Source Software, 2022
Scientific Computational Imaging Code (SCICO) is a Python package for solving the inverse problems that arise in scientific imaging applications. Its primary focus is providing methods for solving ill-posed inverse problems by using an appropriate prior ...
Thilo Balke, Fernando Davis, Cristina Garcia-Cardona, Soumendu Majee, M. McCann, L. Pfister, B. Wohlberg   +6 more
semanticscholar   +1 more source

Video-rate computational super-resolution and integral imaging at longwave-infrared wavelengths [PDF]

, 2017
We report the first computational super-resolved, multi-camera integral imaging at long-wave infrared (LWIR) wavelengths. A synchronized array of FLIR Lepton cameras was assembled, and computational super-resolution and integral-imaging reconstruction ...
Carles, Guillem, Harvey, Andrew R., Preciado, Miguel A.   +2 more
core   +2 more sources

On the use of deep learning for computational imaging

NanoScience + Engineering, 2020
Deep learning has emerged as a class of optimization algorithms proven to be effective for a variety of inference and decision tasks. Similar algorithms, with appropriate modifications, have also been widely adopted for computational imaging.
G. Barbastathis
semanticscholar   +1 more source