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Keyword: Object recognition
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Open AccessArticle
14 Pages, 751 KB Download PDF

Fuzzy Recognition by Logic-Predicate Network

Advances in Science, Technology and Engineering Systems Journal, Volume 5, Issue 4, Page # 686–699, 2020; DOI: 10.25046/aj050482
Abstract:

The paper presents a description and justification of the correctness of fuzzy recognition by a logic-predicate network. Such a network is designed to recognize complex structured objects that can be described by predicate formulas. The NP-hardness of such an object recognition requires to separate the learning process, leaving it exponentially hard, and the recognition process…

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(This article belongs to the SP9 (Special Issue on Multidisciplinary Innovation in Engineering Science & Technology 2020) & Section Artificial Intelligence in Computer Science (CAI))
Open AccessArticle
9 Pages, 2,162 KB Download PDF

Recognition and Position Estimation for Multiple Labware Transportation Using Kinect V2 and Mobile Robots

Advances in Science, Technology and Engineering Systems Journal, Volume 2, Issue 3, Page # 1218–1226, 2017; DOI: 10.25046/aj0203154
Abstract:

Mobile robots can be used to perform transportation tasks for different objects. These tasks have to be implemented carefully. Therefore, an accurate approach for object recognition and position estimation is required. This work presents a concept for identification and position estimation of multiple labware. These labware, which contain chemical and biological components, have to be…

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(This article belongs to the SP3 (Special issue on Recent Advances in Engineering Systems 2017) & Section Robotics (ROB))
Open AccessArticle
7 Pages, 1,426 KB Download PDF

SIFT Implementation based on LEON3 Processor

Advances in Science, Technology and Engineering Systems Journal, Volume 6, Issue 1, Page # 1257–1263, 2021; DOI: 10.25046/aj0601143
Abstract:

This paper proposes a new method of implementation of the part of SIFT (Scale-Invariant Feature Transform) algorithm used to extract the feature of an image of a size 256×256 of pixels, which is mainly based on the using the LEON3 soft core processor .With this method it is possible to detect points of interest and…

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(This article belongs to Section Electrical Engineering (ELE))
Open AccessArticle
11 Pages, 4,960 KB Download PDF

NAO Humanoid Robot Obstacle Avoidance Using Monocular Camera

Advances in Science, Technology and Engineering Systems Journal, Volume 5, Issue 1, Page # 274–284, 2020; DOI: 10.25046/aj050135
Abstract:

In this paper, we present an experimental approach that allows a humanoid robot to effectively plan and execute whole body motions, like climbing obstacles and straight stairs up or down, besides jumping over obstacles using only on-board sensing. Re- liable and accurate motion sequence for humanoid employed in complex indoor en- vironments is a necessity…

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(This article belongs to Section Artificial Intelligence in Computer Science (CAI))
Open AccessArticle
11 Pages, 2,371 KB Download PDF

Grasping and Placing Operation for Labware Transportation in Life Science Laboratories using Mobile Robots

Advances in Science, Technology and Engineering Systems Journal, Volume 2, Issue 3, Page # 1227–1237, 2017; DOI: 10.25046/aj0203155
Abstract:

In automated working environments, mobile robots can be used for different purposes such as material handling, domestic services, and objects transportation. This work presents a grasping and placing operation for multiple labware and tube racks in life science laboratories using the H20 mobile robots. The H20 robot has dual arms where each arm consists of…

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(This article belongs to the SP3 (Special issue on Recent Advances in Engineering Systems 2017) & Section Automation & Control Systems (ACS))
Open AccessArticle
15 Pages, 290 KB Download PDF

Advances in Optimisation Algorithms and Techniques for Deep Learning

Advances in Science, Technology and Engineering Systems Journal, Volume 5, Issue 5, Page # 563–577, 2020; DOI: 10.25046/aj050570
Abstract:

In the last decade, deep learning(DL) has witnessed excellent performances on a variety of problems, including speech recognition, object recognition, detection, and natural language processing (NLP) among many others. Of these applications, one common challenge is to obtain ideal parameters during the training of the deep neural networks (DNN). These typical parameters are obtained by…

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(This article belongs to Section Interdisciplinary Applications of Computer Science (CSI))

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