Evolving collective cognition for object identification in foraging robotic swarms

2020 ◽  
Author(s):  
Motoaki Hiraga ◽  
Yufei Wei ◽  
Kazuhiro Ohkura
Keyword(s):  
Object Identification ◽  
Robotic Swarms ◽  
Collective Cognition

Editorial

2017 ◽  
Author(s):  
Vu Chi Kien ◽  
Do Ngoc Minh ◽  
Nguyen Hoang Ha ◽  
Nguyen Linh Trung
Keyword(s):  
Good Practice ◽  
Scientific Publication ◽  
Associate Editor ◽  
Open Access Journal ◽  
Object Identification ◽  
Online Journal ◽  
International Visibility ◽  
National University ◽  
Standard Practices

Dear readers,The year 2017 marks the 55th anniversary of the Journal of Information & Communications of the Ministry of Information and Communications, and the 18th anniversary of its scientific publication – the Research and Development on Information and Communication Technology (RD-ICT) journal. Again, the purpose of RD-ICT is to provide a forum for researchers and professionals to disseminate original and innovative ideas in the fields of information technology, communications and electronics in Vietnam and worldwide.Without kind support and invaluable contribution of readers and authors, and hard work of the anonymous reviewers and editors under the former editorship of Prof. Nguyễn Thúc Hải, Prof. Trần Văn Lộc and Prof. Nguyễn Cảnh Tuấn, RD-ICT would not be what it is today – a total of 37 issues in Vietnamese and 14 issues in English.To contribute to the development of research in Vietnam, toward standard practices, high quality and international visibility, RD-ICT has been taking measures by following current practices of prestigious international research journals. In this editorial, we would like to inform you some of the things we have been doing lately.Since June 2014, RD-ICT has applied online journal management and publishing, thanks to the well-known open-source Open Journal System of the Public Knowledge Project, which is used by thousands of online scientific journals worldwide. The editorial board of RD-ICT is currently being extended to include international prominent scientists, thus forming a team of international associate editors, under the complementary technical editorship of Prof. Đỗ Ngọc Minh (University of Illinois at Urbana-Champaign, United States), Prof. Nguyễn Hoàng Hà (University of Saskatchewan, Canada) and Prof. Nguyễn Linh Trung (Vietnam National University, Hanoi). Each submission is now assigned to an associate editor who then coordinates the review process and makes editorial decision.For improved paper quality in terms of organization and presentation, authors are guided to good practice of technical paper writing. In addition, accepted submissions are now copy-edited, by the corresponding associate editors, and laid out using LATEX.Apart from already being an open-access journal, RD-ICT is also looking into other measures to increase its visibility, such as all-English publishing, digital object identification, Google Scholar citation, and SCOPUS indexing.Taking the opportunity of informing the above changes, we would like to, again, express our sincere gratitude and appreciation to the readers, authors, reviewers and editors of RD-ICT, and to the leadership of the Ministry of Information and Communications and its predecessors – the Directorate General of Posts and Telecommunications, the Ministry of Post and Telecommunications – for their continued support and contribution to RD-ICT.We look forward to your comments and feedback for better developing the RD-ICT journal for Vietnam.Sincerely,Vũ Chí Kiên, Editor-in-ChiefĐỗ Ngọc Minh, Nguyễn Hoàng Hà, Nguyễn Linh Trung, Technical Editors-in-Chief

ON METHODS OF OBJECT DETECTION IN VIDEO STREAMS

2017 ◽  
Vol 2 (1) ◽  
pp. 80-87
Author(s):  
Puyda V. ◽  
◽  
Stoian. A.
Keyword(s):  
Computer Vision ◽  
Object Detection ◽  
Open Source ◽  
Feature Detection ◽  
Video Stream ◽  
Object Identification ◽  
Vision Systems ◽  
Modern Computer ◽  
Computer Vision Systems ◽  
Open Source Hardware

Detecting objects in a video stream is a typical problem in modern computer vision systems that are used in multiple areas. Object detection can be done on both static images and on frames of a video stream. Essentially, object detection means finding color and intensity non-uniformities which can be treated as physical objects. Beside that, the operations of finding coordinates, size and other characteristics of these non-uniformities that can be used to solve other computer vision related problems like object identification can be executed. In this paper, we study three algorithms which can be used to detect objects of different nature and are based on different approaches: detection of color non-uniformities, frame difference and feature detection. As the input data, we use a video stream which is obtained from a video camera or from an mp4 video file. Simulations and testing of the algoritms were done on a universal computer based on an open-source hardware, built on the Broadcom BCM2711, quad-core Cortex-A72 (ARM v8) 64-bit SoC processor with frequency 1,5GHz. The software was created in Visual Studio 2019 using OpenCV 4 on Windows 10 and on a universal computer operated under Linux (Raspbian Buster OS) for an open-source hardware. In the paper, the methods under consideration are compared. The results of the paper can be used in research and development of modern computer vision systems used for different purposes. Keywords: object detection, feature points, keypoints, ORB detector, computer vision, motion detection, HSV model color

Symbolic Representation Based Approach for Object Identification in Infrared Images

2017 ◽  
Vol 9 (3) ◽  
pp. 235-240
Author(s):  
Shimoga N. B. Bhushan ◽  
. Harisha ◽  
Arti Pawar ◽  
. Vidyalakshmi
Keyword(s):  
Symbolic Representation ◽  
Object Identification ◽  
Infrared Images

scholarly journals VAGADRONE: Intelligent and Fully Automatic Drone Based on Raspberry Pi and Android

2021 ◽  
Vol 11 (7) ◽  
pp. 3153
Author(s):  
Saifeddine Benhadhria ◽  
Mohamed Mansouri ◽  
Ameni Benkhlifa ◽  
Imed Gharbi ◽  
Nadhem Jlili
Keyword(s):  
Remote Control ◽  
Autonomous Navigation ◽  
Object Identification ◽  
External Control ◽  
Raspberry Pi ◽  
Optimal Trajectories ◽  
Live Streaming ◽  
Wide Range ◽  
Fully Automatic ◽  
Direct Use

Multirotor drones are widely used currently in several areas of life. Their suitable size and the tasks that they can perform are their main advantages. However, to the best of our knowledge, they must be controlled via remote control to fly from one point to another, and they can only be used for a specific mission (tracking, searching, computing, and so on). In this paper, we intend to present an autonomous UAV based on Raspberry Pi and Android. Android offers a wide range of applications for direct use by the UAV depending on the context of the assigned mission. The applications cover a large number of areas such as object identification, facial recognition, and counting objects such as panels, people, and so on. In addition, the proposed UAV calculates optimal trajectories, provides autonomous navigation without external control, detects obstacles, and ensures live streaming during the mission. Experiments are carried out to test the above-mentioned criteria.

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