scholarly journals Using syntactic methods and LSTM to the recognition of objects visual patterns

2019 ◽  
Author(s):  
Gilberto Astolfi ◽  
Vanessa Aparecida de Moares Weber ◽  
Adair Da Silva Oliveira Junior ◽  
Geazy Vilharva Menezes ◽  
Nícolas Alessandro de Souza Belete ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Relevant Information ◽  
Aerial Images ◽  
New Approach ◽  
Visual Patterns ◽  
Aerial Vehicle ◽  
Recognition Of Objects ◽  
F Measure

In this paper, we have designed a new approach to represent and recognize objects visual patterns using syntactic methods. We capture relevant information from an object and associate them with symbols of an alphabet. After that, we derive a string from the object and in put it to LSTM. The idea is to train LSTM with objects visual patterns encapsulated in the strings. We conducted an experiment using soybean crops aerial images captured by an Unmanned Aerial Vehicle (UAV), and we reached an average F-measure of 91%.

scholarly journals Recent Advances in Unmanned Aerial Vehicle Forest Remote Sensing—A Systematic Review. Part I: A General Framework

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 327 ◽  
Author(s):  
Riccardo Dainelli ◽  
Piero Toscano ◽  
Salvatore Filippo Di Gennaro ◽  
Alessandro Matese
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Relevant Information ◽  
Forest Monitoring ◽  
Machine Learning Techniques ◽  
Planted Forests ◽  
Systematic Analysis ◽  
Aerial Photogrammetry ◽  
Wide Range ◽  
Aerial Vehicle

Natural, semi-natural, and planted forests are a key asset worldwide, providing a broad range of positive externalities. For sustainable forest planning and management, remote sensing (RS) platforms are rapidly going mainstream. In a framework where scientific production is growing exponentially, a systematic analysis of unmanned aerial vehicle (UAV)-based forestry research papers is of paramount importance to understand trends, overlaps and gaps. The present review is organized into two parts (Part I and Part II). Part II inspects specific technical issues regarding the application of UAV-RS in forestry, together with the pros and cons of different UAV solutions and activities where additional effort is needed, such as the technology transfer. Part I systematically analyzes and discusses general aspects of applying UAV in natural, semi-natural and artificial forestry ecosystems in the recent peer-reviewed literature (2018–mid-2020). The specific goals are threefold: (i) create a carefully selected bibliographic dataset that other researchers can draw on for their scientific works; (ii) analyze general and recent trends in RS forest monitoring (iii) reveal gaps in the general research framework where an additional activity is needed. Through double-step filtering of research items found in the Web of Science search engine, the study gathers and analyzes a comprehensive dataset (226 articles). Papers have been categorized into six main topics, and the relevant information has been subsequently extracted. The strong points emerging from this study concern the wide range of topics in the forestry sector and in particular the retrieval of tree inventory parameters often through Digital Aerial Photogrammetry (DAP), RGB sensors, and machine learning techniques. Nevertheless, challenges still exist regarding the promotion of UAV-RS in specific parts of the world, mostly in the tropical and equatorial forests. Much additional research is required for the full exploitation of hyperspectral sensors and for planning long-term monitoring.

scholarly journals Utilizing drone technology in the civil engineering

2019 ◽  
Vol 14 (1) ◽  
pp. 27-37
Author(s):  
Matúš Tkáč ◽  
Peter Mésároš
Keyword(s):  
Real Time ◽  
Unmanned Aerial Vehicle ◽  
Civil Engineering ◽  
Aerial Images ◽  
General Overview ◽  
Aerial Photogrammetry ◽  
Different Types ◽  
Aerial Vehicle

Abstract An unmanned aerial vehicle (UAVs), also known as drone technology, is used for different types of application in the civil engineering. Drones as a tools that increase communication between construction participants, improves site safety, uses topographic measurements of large areas, with using principles of aerial photogrammetry is possible to create buildings aerial surveying, bridges, roads, highways, saves project time and costs, etc. The use of UAVs in the civil engineering can brings many benefits; creating real-time aerial images from the building objects, overviews reveal assets and challenges, as well as the broad lay of the land, operators can share the imaging with personnel on site, in headquarters and with sub-contractors, planners can meet virtually to discuss project timing, equipment needs and challenges presented by the terrain. The aim of this contribution is to create a general overview of the use of UAVs in the civil engineering. The contribution also contains types of UAVs used for construction purposes, their advantages and also disadvantages.

Fast Data Acquisition of Aerial Images Using Unmanned Aerial Vehicle System

2014 ◽  
Vol 3 (3) ◽  
pp. 162
Author(s):  
Norhadija Darwin ◽  
Anuar Ahmad
Keyword(s):  
Data Acquisition ◽  
Root Mean Square ◽  
Unmanned Aerial Vehicle ◽  
Large Scale ◽  
Digital Camera ◽  
Aerial Images ◽  
Mean Square ◽  
Fast Data Acquisition ◽  
Vehicle System ◽  
Aerial Vehicle

The present work discusses the technique and methodology of analysing the potential of fast data acquisition of aerial images using unmanned aerial vehicle system. This study utilizes UAV system for large scale mapping by using digital camera attached to the UAV. UAV is developed from the low-altitude photogrammetric mapping to perform the accuracy of the aerial photography and the resolution of the image. The Ground Control Points (GCPs) and Check Points (CPs) are established using Rapid Static techniques through GPS observation for registration purpose in photogrammetric process. The GCPs is used in the photogrammetric processes to produce photogrammetric output while the CP is employed for accuracy assessment. A Pentax Optio W90 consumer digital camera is also used in image acquisition of the aerial photograph. Besides, this study also involves image processing and map production using Erdas Imagine 8.6 software. The accuracy of the orthophoto is determined using the equation of Root Mean Square Error (RMSE). The final result from orthophoto is compared to the ground survey using total station to show the different accuracy of DEM and planimetric survey. It is discovered that root mean square errors obtained from UAV system are ± 0.510, ± 0.564 and ± 0.622 for coordinate x, y and z respectively. Hence, it can be concluded that the accuracy obtained from UAV system is achieved in sub meter. In a nutshell, UAV system has potential use for large scale mapping in field of surveying and other diversified environmental applications especially for small area which has limited time and less man power.

scholarly journals Application of Deep-Learning Methods to Bird Detection Using Unmanned Aerial Vehicle Imagery

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1651 ◽  
Author(s):  
Suk-Ju Hong ◽  
Yunhyeok Han ◽  
Sang-Yeon Kim ◽  
Ah-Yeong Lee ◽  
Ghiseok Kim
Keyword(s):  
Deep Learning ◽  
Unmanned Aerial Vehicle ◽  
Migratory Bird ◽  
Aerial Images ◽  
Aerial Photographs ◽  
Detection Methods ◽  
Single Shot ◽  
Convolutional Network ◽  
Aerial Vehicle ◽  
Bird Detection

Wild birds are monitored with the important objectives of identifying their habitats and estimating the size of their populations. Especially in the case of migratory bird, they are significantly recorded during specific periods of time to forecast any possible spread of animal disease such as avian influenza. This study led to the construction of deep-learning-based object-detection models with the aid of aerial photographs collected by an unmanned aerial vehicle (UAV). The dataset containing the aerial photographs includes diverse images of birds in various bird habitats and in the vicinity of lakes and on farmland. In addition, aerial images of bird decoys are captured to achieve various bird patterns and more accurate bird information. Bird detection models such as Faster Region-based Convolutional Neural Network (R-CNN), Region-based Fully Convolutional Network (R-FCN), Single Shot MultiBox Detector (SSD), Retinanet, and You Only Look Once (YOLO) were created and the performance of all models was estimated by comparing their computing speed and average precision. The test results show Faster R-CNN to be the most accurate and YOLO to be the fastest among the models. The combined results demonstrate that the use of deep-learning-based detection methods in combination with UAV aerial imagery is fairly suitable for bird detection in various environments.

scholarly journals Mapping Reflectance Anisotropy of a Potato Canopy Using Aerial Images Acquired with an Unmanned Aerial Vehicle

2017 ◽  
Vol 9 (5) ◽  
pp. 417 ◽  
Author(s):  
Peter Roosjen ◽  
Juha Suomalainen ◽  
Harm Bartholomeus ◽  
Lammert Kooistra ◽  
Jan Clevers
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Aerial Images ◽  
Reflectance Anisotropy ◽  
Aerial Vehicle

scholarly journals Using Unmanned Aerial Vehicle Remote Sensing and a Monitoring Information System to Enhance the Management of Unauthorized Structures

2019 ◽  
Vol 9 (22) ◽  
pp. 4954
Author(s):  
Yuanrong He ◽  
Weiwei Ma ◽  
Zelong Ma ◽  
Wenjie Fu ◽  
Chihcheng Chen ◽  
...  
Keyword(s):  
Information System ◽  
Unmanned Aerial Vehicle ◽  
Aerial Images ◽  
Surface Model ◽  
Ground Survey ◽  
Elevation Changes ◽  
Aerial Vehicle ◽  
New Construction ◽  
Gis Software ◽  
Interaction Interpretation

In this research, we investigated using unmanned aerial vehicle (UAV) photographic technology to prevent the further expansion of unauthorized construction and thereby reduce postdisaster losses. First, UAV dynamic aerial photography was used to obtain dynamic digital surface model (DSM) data and elevation changes of 2–8 m as the initial sieve target. Then, two periods of dynamic orthophoto images were superimposed for human–computer interaction interpretation, so we could quickly distinguish buildings undergoing expansion, new construction, or demolition. At the same time, mobile geographic information system (GIS) software was used to survey the field, and the information gathered was developed to support unauthorized construction detection. Finally, aerial images, interpretation results, and ground survey information were integrated and released on WebGIS to build a regulatory platform that can achieve accurate management and effectively prevent violations.

scholarly journals Design and construction of a prototype of an unmanned aerial vehicle equipped with artificial vision for the search of people

2017 ◽  
Vol 15 (41) ◽  
pp. 9-26
Author(s):  
Andrés Espinal Rojas ◽  
Andrés Arango Espinal ◽  
Luis Ramos ◽  
Jorge Humberto Erazo Aux
Keyword(s):  
Image Processing ◽  
Unmanned Aerial Vehicle ◽  
Low Cost ◽  
Wireless Transmission ◽  
Image Processing Algorithm ◽  
Image Capture ◽  
Aerial View ◽  
Aerial Vehicle ◽  
Recognition Of Objects ◽  
Technological Challenge

This paper describes the development and implementation of a six-pointed Unmanned Aerial Vehicle [UAV] prototype, designed for finding lost people in hard to access areas, using Arduino MultiWii platform. A platform capable of performing a stable flight to identify people through an on-board camera and an image processing algorithm was developed. Although the use of UAV represents a low cost and quick response –in terms of displacement– solution, capable to prevent or reduce the number of deaths of lost people in away places, also represents a technological challenge, since the recognition of objects from an aerial view is difficult, due to the distance of the UAV to the objective, the UAV’s position and its constant movement. The solution proposed implements an aerial device that performs the image capture, wireless transmission and image processing while it is in a controlled and stable flight.

scholarly journals Rain Gutter Detection in Aerial Images for Aedes aegypti Mosquito Prevention

2020 ◽  
Author(s):  
Lucas Rossi ◽  
André Backes ◽  
Jefferson Souza
Keyword(s):  
Image Processing ◽  
Aedes Aegypti ◽  
Unmanned Aerial Vehicle ◽  
Digital Image Processing ◽  
Yellow Fever ◽  
Automatic System ◽  
Aerial Images ◽  
Aerial Vehicle ◽  
Mosquito Breeding ◽  
Breeding Location

The detection of Aedes aegypti mosquito is essential in the prevention process of serious diseases such as dengue, yellow fever, chikungunya, and Zika virus. Common approaches consist of surveillance agents who need to enter residences to find and eliminate these outbreaks, but often they are unable to do this work due to the absence or resistance of the resident. This paper proposes an automatic system that uses aerial images obtained through a camera coupled from an Unmanned Aerial Vehicle (UAV) to identify rain gutters from a shed that may be mosquitoes’ foci. We use Digital Image Processing (DIP) techniques to differentiate the objects that may or may not be those foci of the mosquito-breeding. The experimental results show that the system is capable of automatically detecting the appropriately mosquito-breeding location.

Assessment of Photogrammetric Micro Fixed-Wing Unmanned Aerial Vehicle (UAV) System For Image Acquisition of Coastal Area

2014 ◽  
Vol 71 (5) ◽  
Author(s):  
Norhadija Darwin ◽  
Anuar Ahmad ◽  
Zulkarnaini Mat Amin ◽  
Othman Zainon
Keyword(s):  
High Resolution ◽  
Unmanned Aerial Vehicle ◽  
Coastal Area ◽  
Image Acquisition ◽  
Digital Camera ◽  
Image Resolution ◽  
Aerial Images ◽  
Conjugate Points ◽  
Coastal Mapping ◽  
Aerial Vehicle

Fast image acquisition is the most important part for societal impact of a developing country. This paper aims to demonstrate the potential use of micro fixed wing unmanned aerial vehicle (UAV) system attached with high resolution digital camera for coastal mapping. In this study, six strips of aerial images of coastal area was captured using a high resolution compact digital camera known as Canon Power Shot SX230 HS and it has 12 megapixel image resolution. From the aerial images, photogrammetric image processing method is completed to produce mapping outputs such a digital elevation model (DEM) and orthophoto. For accuracy assessment, the coordinates of the selected points in the 3D of stereomodel were compared to the conjugate points observed using GPS and the root mean square error (RMSE) is computed. From this study, the results showed that the achievable RMSE are ± 0.018m, ± 0.013m and ± 0.034m for coordinates X, Y and Z respectively. It will anticipate that the UAV will be used for coastal survey and improve current method of producing with low cost, fast and good accuracy. Finally, the UAV has shown great potential to be used for coastal mapping that require accurate results or products using high resolution camera. 

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