scholarly journals Strategies for generating panoramic video images without information about scene correspondences for multispectral distributed aperture systems

2021 ◽  
Vol 45 (4) ◽  
pp. 589-599
Author(s):  
I.A. Kudinov ◽  
M.B. Nikiforov ◽  
I.S. Kholopov
Keyword(s):  
A Priori ◽  
Region Of Interest ◽  
Regions Of Interest ◽  
Video Images ◽  
Panoramic Video ◽  
Minimum Number ◽  
Priori Information ◽  
The Given ◽  
Analytical Expressions ◽  
Selection Of

We derive analytical expressions for calculating the number of elementary computational operations required to generate several personal regions of interest in a panoramic computer-vision distributed-aperture system using two alternative strategies: strategy 1 involves acquisition of a complete panoramic frame, followed by the selection of personal regions of interest, while with strategy 2 the region of interest is directly formed for each user. The parameters of analytical expressions include the number of cameras in the distributed system, the number of users, and the resolution of panorama and user frames. The formulas obtained for the given parameters make it possible to determine a strategy that would be optimal in terms of a criterion of the minimum number of elementary computational operations for generating multiple personal regions of interest. The region of interest is generated using only a priori information about the internal and external camera parameters, obtained as a result of their photogrammetric calibration with a universal test object, and does not take into account information about scene correspondences at the boundaries of intersecting fields of view.

Innovative Approach to Information Search by Example of a Patent Analysis of an Important Substitution Plan

2020 ◽  
pp. 143-157
Author(s):  
Maria A. Milkova
Keyword(s):  
Information Search ◽  
Topic Modeling ◽  
Cognitive Biases ◽  
A Priori ◽  
Import Substitution ◽  
Innovative Approach ◽  
Iterative Search ◽  
Comprehensive Picture ◽  
Priori Information ◽  
Selection Of

Nowadays the process of information accumulation is so rapid that the concept of the usual iterative search requires revision. Being in the world of oversaturated information in order to comprehensively cover and analyze the problem under study, it is necessary to make high demands on the search methods. An innovative approach to search should flexibly take into account the large amount of already accumulated knowledge and a priori requirements for results. The results, in turn, should immediately provide a roadmap of the direction being studied with the possibility of as much detail as possible. The approach to search based on topic modeling, the so-called topic search, allows you to take into account all these requirements and thereby streamline the nature of working with information, increase the efficiency of knowledge production, avoid cognitive biases in the perception of information, which is important both on micro and macro level. In order to demonstrate an example of applying topic search, the article considers the task of analyzing an import substitution program based on patent data. The program includes plans for 22 industries and contains more than 1,500 products and technologies for the proposed import substitution. The use of patent search based on topic modeling allows to search immediately by the blocks of a priori information – terms of industrial plans for import substitution and at the output get a selection of relevant documents for each of the industries. This approach allows not only to provide a comprehensive picture of the effectiveness of the program as a whole, but also to visually obtain more detailed information about which groups of products and technologies have been patented.

scholarly journals A High-Throughput Analysis Method to Detect Regions of Interest and Quantify Zebrafish Embryo Images

2010 ◽  
Vol 15 (9) ◽  
pp. 1152-1159 ◽  
Author(s):  
Xiaoyan Xu ◽  
Xiaoyin Xu ◽  
Xin Huang ◽  
Weiming Xia ◽  
Shunren Xia
Keyword(s):  
High Throughput ◽  
Neural Development ◽  
Zebrafish Embryo ◽  
A Priori ◽  
Region Of Interest ◽  
Real Data ◽  
Zebrafish Embryos ◽  
High Throughput Analysis ◽  
Single Experiment ◽  
Priori Information

Zebrafish is widely used to understand neural development and model various neurodegenerative diseases. Zebrafish embryos are optically transparent, have a short development period, and can be kept alive in microplates for days, making them amenable to high-throughput microscopic imaging. As a result of high-throughput experiments, a large number of images can be generated in a single experiment, posing a challenge to researchers to analyze them efficiently and quantitatively. In this work, we develop an image processing focused on detecting and quantifying pigments in zebrafish embryos. The algorithm automatically detects a region of interest (ROI) enclosing an area around the pigments and then segment the pigments for quantification. In this process, the algorithm identifies the head and torso at first, and then finds the boundaries corresponding to the back and abdomen by taking advantage of a priori information about the anatomy of zebrafish embryos. The method is robust in terms that it can detect and quantify pigments even when the embryos have different orientations and curvatures. We used real data to demonstrate the performance of the method to extract phenotypic information from zebrafish embryo images and compared its results with manual analysis for verification.

scholarly journals Improved Faster R-CNN Traffic Sign Detection Based on a Second Region of Interest and Highly Possible Regions Proposal Network

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2288 ◽  
Author(s):  
Faming Shao ◽  
Xinqing Wang ◽  
Fanjie Meng ◽  
Jingwei Zhu ◽  
Dong Wang ◽  
...  
Keyword(s):  
A Priori ◽  
Region Of Interest ◽  
Traffic Sign ◽  
Detection Systems ◽  
Proposal A ◽  
Sign Detection ◽  
Priori Information ◽  
Small Targets ◽  
Traffic Sign Detection ◽  
Classification Capability

Traffic sign detection systems provide important road control information for unmanned driving systems or auxiliary driving. In this paper, the Faster region with a convolutional neural network (R-CNN) for traffic sign detection in real traffic situations has been systematically improved. First, a first step region proposal algorithm based on simplified Gabor wavelets (SGWs) and maximally stable extremal regions (MSERs) is proposed. In this way, the region proposal a priori information is obtained and will be used for improving the Faster R-CNN. This part of our method is named as the highly possible regions proposal network (HP-RPN). Second, in order to solve the problem that the Faster R-CNN cannot effectively detect small targets, a method that combines the features of the third, fourth, and fifth layers of VGG16 to enrich the features of small targets is proposed. Third, the secondary region of interest method to enhance the feature of detection objects and improve the classification capability of the Faster R-CNN is proposed. Finally, a method of merging the German traffic sign detection benchmark (GTSDB) and Chinese traffic sign dataset (CTSD) databases into one larger database to increase the number of database samples is proposed. Experimental results show that our method improves the detection performance, especially for small targets.

ALGORITHM FOR SELECTION OF LAUNCH ELEMENTS IN THE PRESENCE OF A PRIORI INFORMATION ABOUT ITS COMPOSITION AND STRUCTURE

2018 ◽  
pp. 114-119
Author(s):  
O. I. Nemykin
Keyword(s):  
Decision Making ◽  
Loss Function ◽  
Selection Process ◽  
A Priori ◽  
Measurement Information ◽  
A Priori Information ◽  
Space Objects ◽  
Alternative Hypotheses ◽  
Priori Information ◽  
Selection Of

Traditional methods of the theory of statistical solutions are developed for cases of making single-valued two-alternative or multialternative solutions about the class of an object. Assuming the possibility of ambiguous multi-alternative (in the case of solving the problem of selection of space objects of three-alternative) decisions on the classification of of space objects at the stages of the selection process, a modification of the traditional statistical decision making algorithm is required. Such a modification of the algorithm can be carried out by appropriate selection of the loss function. In the framework of the Bayes approach, an additive loss function is proposed, the structure of which takes into account a priori information on the structure and composition of launch elements in relation to the classes «Launch vehicle» and «spacecraft». The algorithm of decision making is synthesized under the conditions of a priori certainty regarding the probabilistic description of the analyzed situation. It is shown that the problem of verifying three-alternative hypotheses can be reduced to an independent verification of three two-alternative hypotheses, which makes it possible to take particular solutions in the solution process and use a different set of the signs of selection for the formation of solutions for individual classes of space objects. The peculiarities of the implementation of the selection algorithm are discussed in the presence of a priori information and measurement information on starts of a limited volume. The synthesized Bayesian decision making algorithm has the properties necessary to solve the problem of selection of space objects at launch in real conditions in the presence of measuring information specified in the form of a training sample. Its architecture allows to form unambiguous and ambiguous decisions about each space object in the launch.

scholarly journals ALGORITHMS OF SEAFLOOR INDUSTRIAL MACHINERY INSPECTION USING AUV

2020 ◽  
Author(s):  
А.В. Инзарцев ◽  
М.А. Панин ◽  
В.А. Бобков
Keyword(s):  
Autonomous Underwater Vehicles ◽  
A Priori ◽  
Laser Scanner ◽  
Final Model ◽  
New Information ◽  
Object Based ◽  
Object Inspection ◽  
Priori Information ◽  
Available Information ◽  
The Given

АНПА могут быть применены для автоматизированной инспекции объектов подводных добычных комплексов. При наличии априорной информации об объекте (его модели) целью обследования может быть детальная фотосъемка заданных фрагментов объекта. Для выхода АНПА к этим фрагментам используются алгоритмы точной навигационной привязки к объекту на базе анализа последовательности стереоизображений и имеющейся информации о расположении характерных точек объекта. В случае отсутствия априорной информации целью обследования может быть построение детальной 3D модели объекта (с помощью лазерного сканера или многолучевого эхолокатора). Для этого АНПА производит первоначальное обнаружение (локализацию) объекта. Далее его траектория формируется динамически от одной видовой позиции к другой по мере поступления новой информации об объекте. В качестве критерия при выборе очередной видовой позиции используется оценка ее информативности (т.е. объем получаемой новой информации об объекте). Итоговая модель объекта формируется по собранной информации с использованием методов фотограмметрии. В работе рассматриваются подходы и алгоритмы, которые могут быть использованы при обследовании объектов для этих двух случаев. Autonomous underwater vehicles (AUV) can be used for automatized inspection of the objects of marine mining complexes. If a priori information about the object (or its model) is available, the examination can be aimed at detailed photographing the given fragments of the object. Routing AUV to these fragments relies on algorithms of precise navigation referencing to the object based on analysis of the sequence of stereo images and available information about specific points of the object. In case of the necessary information absence, the inspection may target the goal of building the detailed 3D model of the object (using a laser scanner or multibeam echosounder). In that case, AUV performs the initial detection (localization) of the object at first. Then its motion trajectory is generated dynamically from one view position to another as new information about the object becomes available. A criterion of the viewing position selection used is its informational value (i.e., the amount of further information received about the object). The final model is built using gathered information processed with methods of photogrammetry. The paper considers approaches and algorithms applicable for object inspection in two above described cases.

scholarly journals Bayesian Perspective in the Selection of Bean Genotypes

2020 ◽  
Vol 12 (9) ◽  
pp. 173
Author(s):  
Tâmara Rebecca A. de Oliveira ◽  
Moysés Nascimento ◽  
Paulo R. Santos ◽  
Kleyton Danilo S. Costa ◽  
Thalyson V. Lima ◽  
...  
Keyword(s):  
Bayesian Method ◽  
Block Design ◽  
A Priori ◽  
A Priori Information ◽  
Bayesian Procedure ◽  
R Software ◽  
Randomized Block Design ◽  
Priori Information ◽  
Selection Of

Changes in the relative performance of genotypes have made it necessary for more in-depth investigations to be carried out through reliable analyses of adaptability and stability. The present study was conducted to compare the efficiency of different informative priors in the Bayesian method of Eberhart & Russel with frequentist methods. Fifteen black-bean genotypes from the municipalities of Belém do São Francisco and Petrolina (PE, Brazil) were evaluated in 2011 and 2012 in a randomized-block design with three replicates. Eberhart & Russel’s methodology was applied using the GENES software and the Bayesian procedure using the R software through the MCMCregress function of the MCMCpack package. The quality of Bayesian analysis differed according to the a priori information entered in the model. The Bayesian approach using frequentist analysis had greater accuracy in the estimate of adaptability and stability, where model 1 which uses the a priori information, was the most suitable to obtain reliable estimates according to the BayesFactor function. The inference, using information from previous studies, showed to be imprecise and equivalent to the linear-model methodology. In addition, it was realized that the input of a priori information is important because it increases the quality of the adjustment of the model.

scholarly journals Model and method development for determining the completeness of information for remote detection of landmarks for autonomous mobile robots

2021 ◽  
Vol 6 (2(62)) ◽  
pp. 37-41
Author(s):  
Oleksandr Poliarus ◽  
Andrii Lebedynskyi ◽  
Yevhenii Chepusenko ◽  
Nina Lyubymova
Keyword(s):  
Method Development ◽  
A Priori ◽  
Weather Conditions ◽  
Threshold Level ◽  
Remote Detection ◽  
Measurement Information ◽  
Priori Information ◽  
The Given ◽  
Physical Principles ◽  
Approach Unity

The object of research is the completeness of information for making a navigation decision by an autonomous mobile robot when it performs a task in an unfamiliar area without GPS. It is difficult to identify a landmark in the absence and abundance of information. One of the most problematic places is the mathematical description of the criterion according to which an autonomous robot makes a decision about the completeness of information. The paper substantiates a model and method for determining the completeness of information by a robot equipped with several landmarks detection tools operating on different physical principles. It is shown that the implementation of the method requires a priori information on the probability of detecting various landmarks by passive and active means against a continuous and discontinuous background at different illumination of objects, in day and night conditions under different weather conditions. The values of the probability of detecting a specific type of landmark obtained in such studies serve as the basis for constructing an information cadastre for a job performing tasks on the ground. Three formulas are proposed for determining the coefficient of completeness of information, taking into account a priori and a posteriori inventories, and recommended areas of application. The value of this coefficient depends on the threshold level of the probability of detecting a landmark. The reliability of a decision made by a robot is greatest when it is made under conditions of a certain level of completeness of information. The proposed method can be used for other technical objects from which the measurement information is received. Compared with the known methods, it expands the boundaries of application and reveals the possibility of assessing the completeness of information in constantly changing conditions. Along with a change in these conditions, the characteristics of the completeness of information also change. The coefficient of completeness of information can approach unity even in the absence of separate means of detecting landmarks, and then the method makes it possible to assess the need for their use in the given conditions.

MEASUREMENT AS ABDUCTION

2021 ◽  
pp. 1-26
Author(s):  
Roman Z. Morawski
Keyword(s):  
Inverse Problems ◽  
A Priori ◽  
Abductive Reasoning ◽  
Measuring System ◽  
A Priori Information ◽  
The Core ◽  
Measurement Results ◽  
Priori Information ◽  
Resolution Spectrometer ◽  
Selection Of

Abstract It is argued, in this paper, that the core operation underlying any measurement – the inverse modelling under uncertainty – is equivalent to quantitative abductive reasoning which consists in the selection of the best estimate of a measurand (i.e. a quantity to be measured) in a set of admissible solutions, using a priori information: (i) on the measurand, (ii) on the measuring system coupled with an object under measurement, and (iii) on the influence of the environment including the user of the measurement results. There are two key premises of this claim: a systematic interpretation of measurement in terms of inverse problems, proposed earlier by the author, and a logical link between inverse problems and abduction, identified by the Finnish philosopher of science Ilkka Niiniluoto. The title claim of this paper is illustrated with an expanded example of measuring optical spectrum by means of a low-resolution spectrometer.

Selection of processing parameters for solving the 3D inverse problem of gravity exploration by the discrete Fourier transform method in GIS INTEGRO

2021 ◽  
pp. 47-52
Author(s):  
Nadezhda Pimanova ◽  
Viktor Spiridonov
Keyword(s):  
Inverse Problem ◽  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
A Priori ◽  
Processing Parameters ◽  
Effective Density ◽  
Transform Method ◽  
Optimal Values ◽  
Priori Information ◽  
Selection Of

In GIS INTEGRO, a program using the discrete Fourier transform is created to solve the 3D inverse problem of gravimetry. The result of its work is a 3D distribution of the effective density. The program allows to use an extended parametrization of the form: fα,β(r,x) = f(r,zα)|z|–β. By changing the parameters α — "depth multiplier" — and β — "exponent at z"— one can obtain various equivalent distributions of effective densities and choose the most appropriate one based on a priori information. The experience of solving the 3D inverse problem by this method with different set values of these parameters allowed us to recommend the optimal values. As a criterion for choosing a solution from a variety of possible solutions, it is proposed to use a comparison of them with the data of seismic studies of the DDS and the CCP.

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