Optimal design of an earth observation optical system with dual spectral and high resolution

2017 ◽  
Author(s):  
Pei-pei Yan ◽  
Kai Jiang ◽  
Kai Liu ◽  
Jing Duan ◽  
Qiusha Shan
Keyword(s):  
High Resolution ◽  
Optimal Design ◽  
Optical System ◽  
Earth Observation

scholarly journals 2nd Edition of Instrumenting Smart City Applications with Big Sensing and Earth Observatory Data: Tools, Methods and Techniques

2021 ◽  
Vol 13 (7) ◽  
pp. 1310
Author(s):  
Gabriele Bitelli ◽  
Emanuele Mandanici
Keyword(s):  
High Resolution ◽  
Exponential Growth ◽  
Smart City ◽  
Earth Observation ◽  
Urban Environments ◽  
Observation Data ◽  
High Resolution Imagery ◽  
Observatory Data ◽  
Methods And Techniques ◽  
Earth Observation Data

The exponential growth in the volume of Earth observation data and the increasing quality and availability of high-resolution imagery are increasingly making more applications possible in urban environments [...]

scholarly journals Detecting and locating light atoms from high-resolution STEM images: The quest for a single optimal design

2016 ◽  
Vol 170 ◽  
pp. 128-138 ◽  
Author(s):  
J. Gonnissen ◽  
A. De Backer ◽  
A.J. den Dekker ◽  
J. Sijbers ◽  
S. Van Aert
Keyword(s):  
High Resolution ◽  
Optimal Design ◽  
Light Atoms

Design of low altitude high resolution lidar optical system

2021 ◽  
Vol 50 (1) ◽  
pp. 20200117-20200117
Author(s):  
刘壮 Zhuang Liu ◽  
王超 Chao Wang ◽  
江伦 Lun Jiang ◽  
史浩东 Haodong Shi
Keyword(s):  
High Resolution ◽  
Optical System ◽  
Low Altitude

Design of refocusing system for a high resolution TDICCD earth observation camera

2015 ◽  
Vol 8 (6) ◽  
pp. 1013-1019
Author(s):  
吕世良 L Shi-liang ◽  
刘金国 LIU Jin-guo ◽  
王晓茜 WANG Xiao-qian
Keyword(s):  
High Resolution ◽  
Earth Observation

scholarly journals Domain Knowledge-Assisted Automatic Diagnosis of Idiopathic Pulmonary Fibrosis (IPF) Using High Resolution Computed Tomography (HRCT) (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13979-13980
Author(s):  
Wenxi Yu ◽  
Hua Zhou ◽  
Jonathan G. Goldin ◽  
Grace Hyun J. Kim
Keyword(s):  
Computed Tomography ◽  
High Resolution ◽  
Optimal Design ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Domain Knowledge ◽  
Population Level ◽  
Design Criterion ◽  
High Resolution Computed Tomography ◽  
Ct Slices

Domain knowledge acquired from pilot studies is important for medical diagnosis. This paper leverages the population-level domain knowledge based on the D-optimal design criterion to judiciously select CT slices that are meaningful for the disease diagnosis task. As an illustrative example, the diagnosis of idiopathic pulmonary fibrosis (IPF) among interstitial lung disease (ILD) patients is used for this work. IPF diagnosis is complicated and is subject to inter-observer variability. We aim to construct a time/memory-efficient IPF diagnosis model using high resolution computed tomography (HRCT) with domain knowledge-assisted data dimension reduction methods. Four two-dimensional convolutional neural network (2D-CNN) architectures (MobileNet, VGG16, ResNet, and DenseNet) are implemented for an automatic diagnosis of IPF among ILD patients. Axial lung CT images are acquired from five multi-center clinical trials, which sum up to 330 IPF patients and 650 non-IPF ILD patients. Model performance is evaluated using five-fold cross-validation. Depending on the model setup, MobileNet achieved satisfactory results with overall sensitivity, specificity, and accuracy greater than 90%. Further evaluation of independent datasets is underway. Based on our knowledge, this is the first work that (1) uses population-level domain knowledge with optimal design criterion in selecting CT slices and (2) focuses on patient-level IPF diagnosis.

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