Neural Networks As A Tool For Pattern Recognition of Fasteners

Al-Sharo, Yasser Mohammad; Abu-Jassar, Amer Tahseen; Sotnik, Svitlana; Lyashenko, Vyacheslav

doi:10.14445/22315381/ijett-v69i10p219

Cited by 3 publications

(3 citation statements)

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“…ANN has been applied in a wide range of fields, including search optimization [ 134 ], pattern recognition [ 135 , 136 ], image processing [ 137 , 138 ], mobile robot routing [ 139 ], signal processing [ 140 ], and many more. A hybrid approach to mobile robot navigation combining an ANN and FL [ 141 , 142 ] was designed for a mobile robot navigation controller using a neuro-fuzzy logic system.…”

Section: Heuristic Approachmentioning

confidence: 99%

Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot

Katona,

Neamah,

Korondi

2024

Sensors

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Path planning creates the shortest path from the source to the destination based on sensory information obtained from the environment. Within path planning, obstacle avoidance is a crucial task in robotics, as the autonomous operation of robots needs to reach their destination without collisions. Obstacle avoidance algorithms play a key role in robotics and autonomous vehicles. These algorithms enable robots to navigate their environment efficiently, minimizing the risk of collisions and safely avoiding obstacles. This article provides an overview of key obstacle avoidance algorithms, including classic techniques such as the Bug algorithm and Dijkstra’s algorithm, and newer developments like genetic algorithms and approaches based on neural networks. It analyzes in detail the advantages, limitations, and application areas of these algorithms and highlights current research directions in obstacle avoidance robotics. This article aims to provide comprehensive insight into the current state and prospects of obstacle avoidance algorithms in robotics applications. It also mentions the use of predictive methods and deep learning strategies.

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Section: Heuristic Approachmentioning

confidence: 99%

Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot

Katona,

Neamah,

Korondi

2024

Sensors

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“…Then geometric mean in each row of the matrix is determined by expression (3), and the sum of geometric means is determined by expression (5) and is equal to 12,6. In sum, let all values of weighting coefficients be equal to 1; that is, ∑ 𝜇 𝑖 = 1 evaluated as equivalent, we get weighting coefficient values that can characterize each criterion's importance.…”

Section: Implementation Of a System For Managing Access To Rss Based ...mentioning

confidence: 99%

“…Currently, robotics is very actively developing [1][2][3][4][5][6]. Aviation, household, military, space, medical, underwater, industrial, and construction robotics exist.…”

Section: Introductionmentioning

confidence: 99%

Access Control to Robotic Systems Based on Biometric: The Generalized Model and its Practical Implementation

2023

IJIES

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The paper presents a generalized system's structural scheme and components for monitoring and controlling access to robotic systems based on biometric data for decision-making. Mathematical decision-making models for choosing the best alternative based on fuzzy sets are proposed. The fuzzy analytical hierarchy process determined weights of 6 criteria (for k1 criterion weighting factor is equal to 2.2; for k2 criterion -1.8; for k3 criterion -0.6; for k4 criterion -0.6; for k5 criterion -0.6; for k6 criterion -0.2, that is, most weighty would be k1recognition accuracy) against which the best option was evaluated. Thus, during evaluation of alternative on six criteria it was obtained that t alternative X1 (face recognition in full-face), will have the key value of membership function of resulting fuzzy set alternatives with ideal value of integral criterion, equal to 0.53, and as result, implemented rational choice, taking into account given criteria. The difference is that we have introduced such criteria as anti-spoofing. The access control system for robotic systems works in real-time. It is implemented based on an algorithmic decision-making complex, which includes two-factor authentication to increase security: registration involves entering employee data from the keyboard (password, login, surname, first name, position) and physiological authentication (identification by face). Face detection is proposed to be implemented on several images: face, profile, face, and profile in the mask. A distinctive feature of our development is that often, a main requirement for "access control systems with facial identification" is the frontal location of the face relative to the camera; in our case, the image of the face at an angle was added.

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Fatty Liver Level Recognition Using Particle Swarm optimization (PSO) Image Segmentation and Analysis

Mousavi¹,

Victorovich

Ilanloo

et al. 2022

2022 12th International Conference on Computer and Knowledge Engineering (ICCKE)

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Neural Networks As A Tool For Pattern Recognition of Fasteners

Cited by 3 publications

References 0 publications

Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot

Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot

Access Control to Robotic Systems Based on Biometric: The Generalized Model and its Practical Implementation

Fatty Liver Level Recognition Using Particle Swarm optimization (PSO) Image Segmentation and Analysis

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