Two-stage adaptive random Fourier sampling method for image reconstruction

2021 ◽  
Vol 117 ◽  
pp. 107990
Author(s):  
Joo Dong Yun ◽  
Yunho Kim
Keyword(s):  
Image Reconstruction ◽  
Sampling Method ◽  
Two Stage ◽  
Fourier Sampling

A fast edge-based two-stage direct sampling method

2021 ◽  
Vol 150 ◽  
pp. 104742
Author(s):  
Hexiang Bai ◽  
Gregoire Mariethoz
Keyword(s):  
Sampling Method ◽  
Two Stage ◽  
Direct Sampling ◽  
Edge Based

scholarly journals Hot Anchors: A Heuristic Anchors Sampling Method in RCNN-Based Object Detection

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3415 ◽  
Author(s):  
Jinpeng Zhang ◽  
Jinming Zhang ◽  
Shan Yu
Keyword(s):  
Object Detection ◽  
Sampling Method ◽  
Ground Truth ◽  
Detection Accuracy ◽  
Two Stage ◽  
Baseline Model ◽  
Detection Algorithms ◽  
Imbalance Problem ◽  
Image Object Detection ◽  
Image Object

In the image object detection task, a huge number of candidate boxes are generated to match with a relatively very small amount of ground-truth boxes, and through this method the learning samples can be created. But in fact the vast majority of the candidate boxes do not contain valid object instances and should be recognized and rejected during the training and evaluation of the network. This leads to extra high computation burden and a serious imbalance problem between object and none-object samples, thereby impeding the algorithm’s performance. Here we propose a new heuristic sampling method to generate candidate boxes for two-stage detection algorithms. It is generally applicable to the current two-stage detection algorithms to improve their detection performance. Experiments on COCO dataset showed that, relative to the baseline model, this new method could significantly increase the detection accuracy and efficiency.

scholarly journals A study on conceptual associations of colors in preschool children

2019 ◽  
Vol 9 (3) ◽  
pp. 729-764
Author(s):  
Özge Mazlum ◽  
Fehmi Soner Mazlum
Keyword(s):  
Preschool Children ◽  
Working Group ◽  
Sampling Method ◽  
Learning Activities ◽  
Preliminary Review ◽  
Two Stage ◽  
Context Analysis ◽  
Purposive Sampling ◽  
Analysis Technique ◽  
Descriptive Survey

In this study, the conceptual associations of colors in preschool children were examined with an interdisciplinary perspective. Designed as a preliminary review, this study provides insights and suggestions about how conceptual associations of colors can be used for developing products and services for kids and improving the effectiveness of learning activities in education. This study was designed as descriptive survey because it describes an existing situation. This research’s working group was chosen through a purposive sampling method. The study also includes interpreted components. Two-stage interviews were made with 204 children aged between 60 and 72 months in pre-school education in Ankara with active participation of their form teachers, and the data were collected using the context analysis technique. The study found that children show dominant preference for certain colors in connection with certain concepts and they made consistent spectrum preference for certain concepts. These preferences indicate that the children aged between 60 and 72 months are able to make associations between concepts and colors and attribute meanings to colors in the background, with important hints for the use of colors in designing products and planning learning activities for children.

scholarly journals Timber Inventory of Large Acreages Using Stratified Two-Stage List Sampling

2005 ◽  
Vol 29 (3) ◽  
pp. 152-157 ◽  
Author(s):  
Bruce E. Borders ◽  
Barry D. Shiver ◽  
Michael L. Clutter
Keyword(s):  
Forest Inventory ◽  
Sampling Method ◽  
Sampling Effort ◽  
Field Sampling ◽  
Two Stage ◽  
Timber Inventory

Abstract We present two-stage list sampling estimators and methodology that are useful in a forest inventory context. The advantages of this sampling method are discussed and illustrated with an inventory of a 3,419-acre timber tract. In this example, two-stage list sampling resulted in strata level and tract level estimates that were very close to estimates from a more intensive cruise that used twice as much field sampling effort. South. J. Appl. For. 29(3):152–157.

scholarly journals The Determination of Sample Size for Sensitive Issue Successive Survey with the Multiplication RRT Model under Two-Stage and Stratified Two-Stage Random Sampling and Its Application in Medical Survey

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Bo Yu ◽  
Xiaonan Liang ◽  
Ying Wang ◽  
Yun Liu ◽  
Qiao Chang ◽  
...  
Keyword(s):  
Sample Size ◽  
Sampling Method ◽  
Sampling Errors ◽  
Two Stage ◽  
Successive Sampling ◽  
Optimal Sample ◽  
Sensitive Issue ◽  
Survey Accuracy ◽  
The Cost

When designing the sample scheme, it is important to determine the sample size. The survey accuracy and cost of survey and sampling method should be considered comprehensively. In this article, we discuss the method of determining the sample size of complex successive sampling with rotation sample for sensitive issue and deduce the formulas for the optimal sample size under two-stage sampling and stratified two-stage sampling by using Cauchy-Schwartz inequality, respectively, so as to minimize the cost for given sampling errors and to minimize the sampling errors for given cost.

scholarly journals A two-stage sampling method with stratified secondary units.

2000 ◽  
Vol 35 (2) ◽  
pp. 231-236 ◽  
Author(s):  
Ishizue Adachi ◽  
Kohji Yamamura
Keyword(s):  
Sampling Method ◽  
Two Stage

A NOVEL TWO-STAGE GENETIC ALGORITHM FOR IMAGE RECONSTRUCTION OF ELECTRICAL RESISTANCE TOMOGRAPHY

2010 ◽  
Vol 01 (04) ◽  
pp. 523-542
Author(s):  
SANAZ ASGARIFAR ◽  
JAVAD FROUNCHI ◽  
MOHAMMAD HOSSIEN ZARIFI ◽  
AMIN MAHDIZADEH
Keyword(s):  
Genetic Algorithm ◽  
Image Reconstruction ◽  
Electrical Resistance ◽  
Process Time ◽  
Initial Population ◽  
Two Stage ◽  
Electrical Resistance Tomography ◽  
Random Group ◽  
Ill Posed ◽  
Resistivity Inversion

In this paper, we present a combined GA-ERT method based on two-stage genetic algorithm for image reconstruction in electrical resistance tomography (ERT). Image reconstruction in ERT is an ill-posed inverse problem and we have replaced the reverse solver by a two-stage optimization algorithm. The first stage of GA-ERT is reach to an approximate shape and location of the object. Also in this stage, we proposed a new electrode arrangement for ERT forward solver to reduce the process time of the forward problem. In the second stage, the GA employs result of the first stage as an initial population instead of a random group. Therefore with the local zoom, the GA can be employed to obtain the shape and location of the object more precisely. Experimental results of numerically solved ERT by the GA are also presented and compared to those obtained by other more established inversion methods such as modified Newton–Raphson (mNR) and RES2DINV program which is a standard 2-D resistivity inversion program. Results show that the proposed method can efficiently improve the ill-posed condition of ERT image reconstruction problem and can superiorly enhance the quality of ERT images.

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