An Integrated Approach for Table Detection and Structure Recognition

2021 ◽  
Vol 2021 (1) ◽  
pp. 41-50
Author(s):  
Hai-Hong Phan
Keyword(s):  
Real Data ◽  
Integrated Approach ◽  
Difficult Problem ◽  
Structure Identification ◽  
Complex Structures ◽  
Structure Recognition ◽  
Learning Techniques ◽  
Image Processing Algorithms ◽  
Table Data ◽  
Station Record

Detecting and identifying the table structure is an important issue in document digitization. Although there have been many great strides based on current deep learning techniques, table structure identification is still a difficult and difficult problem, especially when solving the problem of digitizing text in practice. The paper proposes a solution to digitize table documents based on the Cascade R-CNN HRNet network to detect, classify tables and integrate image processing algorithms to improve table data identification results. The proposed algorithm proved effective on real data - the hydrometeorological station record book contains tables including simple and complex structures tables with over 98% accuracy.

Analysis of regional economic evaluation based on machine learning

2020 ◽  
pp. 1-11
Author(s):  
Xiaoying Xu ◽  
Zhijian Zeng
Keyword(s):  
Economic Development ◽  
Economic Evaluation ◽  
Regional Economy ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Real Data ◽  
Entropy Weight ◽  
Regional Economic ◽  
Economic Strategy ◽  
Table Data

The regional economic evaluation and analysis has guiding significance for the subsequent economic strategy formulation. Due to the influence of various factors, the volatility of some current economic evaluation models is relatively large. According to the needs of regional economic evaluation, this study uses computer technology combined with regional economic development to build an economic development evaluation model to evaluate and analyze the regional economy. Through comparative analysis, this study selects the entropy weight-TOPSIS model as the comprehensive evaluation model of regional economy, uses the entropy weight method to determine the weight of each index, and then uses the TOPSIS method to conduct comprehensive evaluation. In addition, this study designs a control experiment to analyze the performance of this study model. Moreover, this study uses the model proposed in this study to conduct regional economic evaluation in recent years, and compares it with real data, and observes the test results with statistical charts and table data. The research results show that this research model has a certain effect, which can provide analytical tools for the follow-up economic strategy research and analysis.

scholarly journals Penentu Jarak Tembak Berdasarkan Kerusakan Proyektil Timah Tanpa Jacket untuk Senjata Api Genggam Jenis Revolver S&W Kaliber .38 Spesial pada Target Tulang

2015 ◽  
Vol 17 (3) ◽  
pp. 135
Author(s):  
Sudibyo Sudibyo
Keyword(s):  
Target Location ◽  
Target Position ◽  
Real Data ◽  
Criminal Cases ◽  
Shape Coefficient ◽  
A Value ◽  
Technical Specifications ◽  
Table Data ◽  
Throw Distance ◽  
Test Firing

Abstract This study aims to predict the shooting range based on damage the type of lead a projectile without jacket caliber.38 special fired from handguns kinds brand Revolver S & W caliber .38 specials. Based on the phenomenon of criminal cases of abuse handguns types Revolver and the fact that real data it was found that 8% of the amount of lead projectiles without jacket as forensic evidence, the condition has broken the deformed moderate to severe.         The study was conducted at the Police Forensic Laboratory experimental method test-fired in the shooting box at short throw distance range of 0.5 to 6 meters , where the bone is positioned at the target position changes location every 0.5 meters, so the total number of shots is 12 times shot on 12 position target location, and finally obtained 12 variations of deformation projectile shot results.        Stages test firing conducted through three stages as follows: 1). Phase sample preparation equipment and materials firearms, bullets and target bone. 2). Phase shooting target accurately. 3). Stages of deformation measurements and weighing projectile, arranged in the form of table data.        Material samples of bullet used was the type of lead bullets without jacket caliber .38 special with technical specifications diameter of projectile 9.09 mm (real 9.05 mm), length of projectile 17.90 mm (real 18.61 mm), projectile material lead antimony, projectile weight of 10.25 grams, muzzle velocity (initial) 265 m / sec, rounded nose shape, coefficient of form C = 2, the ballistic coefficient i = 0,9 effective range or the distance accurately of 25 meters.        Material samples of bone were used as target is 1694 SR veal ribs with bone hardness values (87 ± 1.5) shore, is used for the calibration test firing, a human skull age adults (≥ 35 years) with a value of hardness (78 ± 6 ) shore, is used as the target subjects of research, human ribs (costal C-3 / C-6) adult (≥ 35 years) with a value of hardness (69 ± 19.5) shore, is used as the target subjects of research. Keywords : deformation; projectiles; bones

scholarly journals Grammar Guided Genetic Programming for Network Architecture Search and Road Detection on Aerial Orthophotography

2020 ◽  
Author(s):  
Víctor de la Fuente Castillo ◽  
Alberto Díaz-Álvarez ◽  
Miguel-Ángel Manso-Callejo ◽  
Francisco Serradilla García
Keyword(s):  
Genetic Programming ◽  
Network Architecture ◽  
Structural Diversity ◽  
Network Architectures ◽  
Complex Structures ◽  
Road Detection ◽  
Learning Techniques ◽  
Candidate Network ◽  
Optimal Network ◽  
Hidden Layer

Photogrammetry involves aerial photography of the earth’s surface and subsequently processing the images to provide a more accurate depiction of the area (Orthophotography). It’s used by the Spanish Instituto Geográfico Nacional to update road cartography but requires a significant amount of manual labor due to the need to perform visual inspection of all tiled images. Deep Learning techniques (artificial neural networks with more than one hidden layer) can perform road detection but it is still unclear how to find the optimal network architecture. Our system applies grammar guided genetic programming to the search of deep neural network architectures. In this kind of evolutive algorithm all the population individuals (here candidate network architectures) are constrained to rules specified by a grammar that defines valid and useful structural patterns to guide the search process. Grammar used includes well-known complex structures (e.g. Inception-like modules) combined with a custom designed mutation operator (dynamically links the mutation probability to structural diversity). Pilot results show that the system is able to design models for road detection that obtain test accuracies similar to that reached by state of the art models when evaluated over a dataset from the Spanish National Aerial Orthophotography Plan.

Multiparameter analysis of geophysical methods for target detection: The unified geophysical model approach

Geophysics ◽  
2013 ◽  
Vol 78 (6) ◽  
pp. IM1-IM13 ◽  
Author(s):  
C. Orfanos ◽  
G. Apostolopoulos
Keyword(s):  
Target Detection ◽  
Geophysical Methods ◽  
Direct Methods ◽  
Real Data ◽  
Integrated Approach ◽  
Test Site ◽  
Additional Tool ◽  
Void Detection ◽  
Geophysical Model ◽  
Multiparameter Analysis

Void detection is a difficult task for geophysical methods. The main disadvantage is the uncertainty of the final interpretation and the need for verification of the results with direct methods of underground investigation. A good way to reduce this uncertainty, apart from drilling, is through the implementation of more than one geophysical method in the same area. An integrated approach of geophysical methods can be achieved by using multiparameter statistical techniques, such as cluster analysis. Firstly, the effectiveness of multiparameter analysis on synthetic data is studied and then on real data from a controlled test site. In addition, a new approach for the creation of a unified geophysical model (UGM) is suggested to optimize target detection. Finally, the UGM approach is implemented and is evaluated in a real case study for void detection in an urban environment. The UGM offers the integrated information of the geophysical methods that are used without the need for predefined relationships. It is a model resulting from a specific statistical procedure, free of subjective precautions, and easily understood even by nonexperts in geophysics. Finally, it offers an additional tool for the better understanding of the subsurface as far as the difficult task of void detection is concerned.

scholarly journals Vision-Based Multirotor Following Using Synthetic Learning Techniques

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4794
Author(s):  
Alejandro Rodriguez-Ramos ◽  
Adrian Alvarez-Fernandez ◽  
Hriday Bavle ◽  
Pascual Campoy ◽  
Jonathan P. How
Keyword(s):  
Reinforcement Learning ◽  
Object Detection ◽  
Learning Strategies ◽  
Motion Control ◽  
Domain Adaptation ◽  
Control Strategies ◽  
Synthetic Data ◽  
Real Data ◽  
Stable Convergence ◽  
Learning Techniques

Deep- and reinforcement-learning techniques have increasingly required large sets of real data to achieve stable convergence and generalization, in the context of image-recognition, object-detection or motion-control strategies. On this subject, the research community lacks robust approaches to overcome unavailable real-world extensive data by means of realistic synthetic-information and domain-adaptation techniques. In this work, synthetic-learning strategies have been used for the vision-based autonomous following of a noncooperative multirotor. The complete maneuver was learned with synthetic images and high-dimensional low-level continuous robot states, with deep- and reinforcement-learning techniques for object detection and motion control, respectively. A novel motion-control strategy for object following is introduced where the camera gimbal movement is coupled with the multirotor motion during the multirotor following. Results confirm that our present framework can be used to deploy a vision-based task in real flight using synthetic data. It was extensively validated in both simulated and real-flight scenarios, providing proper results (following a multirotor up to 1.3 m/s in simulation and 0.3 m/s in real flights).

3D ZO CRS stack: issues related to complex structures and real data

2003 ◽  
Author(s):  
Antonio Cristini ◽  
Giovanni Cardone ◽  
Paolo Marchetti ◽  
Renzo Zambonini
Keyword(s):  
Real Data ◽  
Complex Structures

A two-step integrated approach to detect differentially expressed genes in RNA-Seq data

2016 ◽  
Vol 14 (06) ◽  
pp. 1650034 ◽  
Author(s):  
Naim Al Mahi ◽  
Munni Begum
Keyword(s):  
Simulation Study ◽  
Negative Binomial ◽  
Real Data ◽  
Integrated Approach ◽  
Differentially Expressed ◽  
Data Sets ◽  
Rna Seq ◽  
Software Packages ◽  
Treatment Conditions ◽  
Integrated Approaches

One of the primary objectives of ribonucleic acid (RNA) sequencing or RNA-Seq experiment is to identify differentially expressed (DE) genes in two or more treatment conditions. It is a common practice to assume that all read counts from RNA-Seq data follow overdispersed (OD) Poisson or negative binomial (NB) distribution, which is sometimes misleading because within each condition, some genes may have unvarying transcription levels with no overdispersion. In such a case, it is more appropriate and logical to consider two sets of genes: OD and non-overdispersed (NOD). We propose a new two-step integrated approach to distinguish DE genes in RNA-Seq data using standard Poisson and NB models for NOD and OD genes, respectively. This is an integrated approach because this method can be merged with any other NB-based methods for detecting DE genes. We design a simulation study and analyze two real RNA-Seq data to evaluate the proposed strategy. We compare the performance of this new method combined with the three [Formula: see text]-software packages namely edgeR, DESeq2, and DSS with their default settings. For both the simulated and real data sets, integrated approaches perform better or at least equally well compared to the regular methods embedded in these [Formula: see text]-packages.

Reliability Evaluation for Binary Directed Tree-Structured Systems Based on Terminal Failure Limit-Value

2011 ◽  
Vol 63-64 ◽  
pp. 268-272
Author(s):  
Wei Chen ◽  
Peng Liu
Keyword(s):  
Reliability Evaluation ◽  
Difficult Problem ◽  
Complex Structures ◽  
Effective Algorithm ◽  
Transitive Relation ◽  
Directed Tree ◽  
Numerical Example ◽  
Structured Systems ◽  
Limit Value ◽  
Set Operations

This paper evaluates reliability of binary directed tree-structured systems based on terminal failure limit-value. For the difficult problem with complex structures and directed transitive relation, the paper describes nodes in the tree system using set algebra, and uses set operations to compute a combinational mode of failed nodes, and then describes it with family of sets. On that basis, an effective algorithm is shown, and a numerical example is given to illustrate the algorithm obtained in the paper.

scholarly journals Personnel Component in Support Anti-crisis Resilience of Business Entities

2020 ◽  
pp. 106-120
Author(s):  
N.E. Kovshun ◽  
V.M. Kostrychenko
Keyword(s):  
Business Processes ◽  
Real Data ◽  
Integrated Approach ◽  
State Enterprise ◽  
Research Assessment ◽  
Practical Implementation ◽  
Strategic Goals ◽  
Business Entities ◽  
Operational Activities ◽  
Functional Components

The paper studies approach to the interpretation of the essence of anti-crisis resilience of business entities and its functional components. The expediency of evaluating crisis resilience because of an integrated approach and taking into account the principles of forming a balanced scorecard is shown. Personnel and staff stability are considered in details which is the ability of the business entity to maintain the flexibility of the management system; reflects its availability of highly qualified personnel, contributes to low staff turnover, reflects the level of motivation of employees. It is proved that taking into account the aspect of the personnel component in the evaluation of the results of the business entity allows to carry out operational activities in accordance with its business strategy. The method of assessing human resources through such indicators as innovation, training, intellectual assets is considered. The list of relevant indicators is determined and the methods of their calculation are shown. Because of real data of the state enterprise “Amber of Ukrain” the approbation of the offered algorithm of an estimation of anti-crisis stability of business entities is carried out. In the process of research assessment was carried out in the context of four forecasts on the following functional components as finance (financial component), clients (marketing component), internal business processes (operational, investment and innovation components), training and staff development (management and information, personnel components)). According to the shaped system of evaluation indicators, standardized and balanced key (aggregated) indicators were calculated for each component of anti-crisis resilience. Based on the level of the overall integrated indicator of crisis resilience on the Harrington scale, the appropriate stage of the crisis process was established. Based on the obtained calculation results, an appropriate system of strategic goals and measures has been developed. It is proved the practical implementation of the system of balanced scores for setting current tasks for each department and employee, taking into account the strategic goals of the business entity.

scholarly journals TEACHING GEOMATICS FOR GEOHAZARD MITIGATION AND MANAGEMENT IN THE COVID-19 TIME

2020 ◽  
Vol XLIV-3/W1-2020 ◽  
pp. 131-138
Author(s):  
M. Scaioni ◽  
L. Longoni ◽  
L. Zanzi ◽  
V. Ivanov ◽  
M. Papini
Keyword(s):  
Case Studies ◽  
Risk Mitigation ◽  
Integrated Approach ◽  
Learning Objectives ◽  
Basic Principles ◽  
Learning Techniques ◽  
Different Types ◽  
Field Campaigns ◽  
First Time ◽  
Academic Year

Abstract. Starting from the Academic Year 2018–2019, Politecnico di Milano university has established a BSc programme on “Civil Engineering for Risk Mitigation” (ICMR). This course is aimed at training students to cope with issues related to different types of natural and anthropogenic hazards, among which Geohazards are paid a primary attention. A “Workshop on Monitoring Techniques for Geohazards” is included to present different Geological, Geophysical and Geodetic techniques to be applied to landslides within an integrated approach. The use of active and problem-based learning techniques was one of the basic principles in the design of ICMR programme. This resulted in planning some visits and field campaigns to allow students to directly work on real case studies. The course has been scheduled for the first time in the second term of A.Y. 2019–2020, when the COVID-19 pandemics developed and prevented the lab activities in the field to be implemented as planned. The paper presents how the content and the organization of the course have been revised to try to reach the same learning objectives notwithstanding the limitations on the activities “in presence”.

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