We present a high-accuracy 3D facial reconstruction system with the following features: real-time 3D facial reconstruction using exposure synchronization multi-camera, feature alignment to quantify facial differences,...
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Biomedical image processing is a hot research topic which helps to majorly assist the disease diagnostic *** the same time,breast cancer becomes the deadliest disease among women and can be detected by the use of diff...
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Biomedical image processing is a hot research topic which helps to majorly assist the disease diagnostic *** the same time,breast cancer becomes the deadliest disease among women and can be detected by the use of different imaging *** mammograms can be used for the earlier identification and diagnostic of breast cancer to minimize the death *** the proper identification of breast cancer has mainly relied on the mammography findings and results to increased false *** resolving the issues of false positives of breast cancer diagnosis,this paper presents an automated deep learning based breast cancer diagnosis(ADL-BCD)model using digital *** goal of the ADL-BCD technique is to properly detect the existence of breast lesions using digital *** proposed model involves Gaussian filter based pre-processing and Tsallis entropy based image *** addition,Deep Convolutional Neural Network based Residual Network(ResNet 34)is applied for feature extraction ***,a hyper parameter tuning process using chimp optimization algorithm(COA)is applied to tune the parameters involved in ResNet 34 *** wavelet neural network(WNN)is used for the classification of digital mammograms for the detection of breast *** ADL-BCD method is evaluated using a benchmark dataset and the results are analyzed under several performance *** simulation outcome indicated that the ADL-BCD model outperforms the state of art methods in terms of different measures.
Two-dimensional transition-metal dichalcogenides (2D TMDCs) are considered promising materials for optoelectronics due to their unique optical and electric properties. However, their potential has been limited by the ...
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Electric vehicles (EV s) boast zero tailpipe emissions, directly improving air quality and lowering greenhouse gas emissions. Despite the promise of EVs for sustainable transportation, their limited range is a key cha...
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This paper presents the control system of the ROMANCAN robot (Gutter Maintenance Robot), a tracked differential mobile robot designed to clean buildings gutters and reduce the risk of operators falling. The focus on t...
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ISBN:
(数字)9798331508807
ISBN:
(纸本)9798331508814
This paper presents the control system of the ROMANCAN robot (Gutter Maintenance Robot), a tracked differential mobile robot designed to clean buildings gutters and reduce the risk of operators falling. The focus on the control system deals with following wall, to correct the robot trajectory in real time. In addition, the integrated electronic components, such as sensors and actuators, are detailed. The simulation results and experimental tests, show the effectiveness of the system in simulated conditions, and with physical prototype, it is noticed at kinematic control that the compensation angle can be computed by dividing 2.5 the initial robot deviation angle; otherwise the dynamic control allows compensate additional real environment disturbs contributing to the field of mobile robotics and automation in narrow spaces at urban environments.
High-precision cylindrical parts are critical components across various industries including aerospace, automotive, and manufacturing. Since these parts play a pivotal role in the performance and safety of the systems...
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Proportional, integral, and derivative (PID) controllers have been widely adopted for industrial applications. However, these controllers are not very efficient for non-linear systems. Artificial neural networks (ANN)...
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ISBN:
(数字)9798350374575
ISBN:
(纸本)9798350374582
Proportional, integral, and derivative (PID) controllers have been widely adopted for industrial applications. However, these controllers are not very efficient for non-linear systems. Artificial neural networks (ANN) based on the Multilayer Perceptron (MLP) have great potential to replace PID controllers due to their polynomial structure, allowing complex non-linear systems to be controlled. This article introduces the integration of four MLPs as alternatives to a traditional PID controller. These MLPs were trained through four bioinspired algorithms tailored for following tasks in mobile robots. The bioinspired algorithms employed for MLP network training include Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Month-Flame Optimization (MFO), and Artificial Hummingbird Algorithm (AHA). A comparative analysis was conducted between these MLPs and a classic PID controller, focusing on parameters such as overshoot (OS), settling time (ST), and steady-state error for different simulated scenarios.
Proportional, integral, and derivative (PID) controllers have been widely adopted for industrial applications. However, these controllers are not very efficient for non-linear systems. Artificial neural networks (ANN)...
Proportional, integral, and derivative (PID) controllers have been widely adopted for industrial applications. However, these controllers are not very efficient for non-linear systems. Artificial neural networks (ANN) based on the Group Method of Data Handling (GMDH) have great potential to replace the PID controllers due to their polynomial structure, allowing complex non-linear systems to be controlled. This work presents a hardware architecture of a GMDH network applied to speed control of a mobile robot platform. The proposed GMDH controller was implemented using a 16-bit floating-point arithmetic representation and was mapped on a Zynq7020 device. A hardware-in-the-loop based on the Universal Direct Memory Access methodology was developed to validate the proposed circuits, allowing for performance comparisons between a classical PID and the GMDH controllers for different simulated scenarios.
Advances in information and communication technologies have significantly transformed engineering education. Virtual laboratories are increasingly adopted to enhance student interaction with control system simulations...
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ISBN:
(数字)9798350391084
ISBN:
(纸本)9798350391091
Advances in information and communication technologies have significantly transformed engineering education. Virtual laboratories are increasingly adopted to enhance student interaction with control system simulations. The improved visualization and interaction capabilities of modern computers offer a more organic way to teach theoretical foundations. This paper describes the implementation of a methodology for teaching control theory that until now was entirely online in a face-to-face environment at the University of the Federal District in Brasilia, Brazil. This methodology utilizes virtual laboratories with CoppeliaSim, MATLAB, and the EVA mobile robot to teach control theory focused on single-input, single-output (SISO) systems for mobile robot tracking and obstacle avoidance applications. The results of the face-to-face implementation are compared to those of the fully online methodology, revealing that in-person teaching significantly enhances the quality of instruction.
In a basketball game, players must act appropriately according to the position and movement of the player. This needs to be learned through team practice. Therefore, if we can build an environment that allows even one...
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