The restoration of museum heritage is an important task with significant cultural and historical value;however, traditional methods of restoration are frequently constrained by the extent of the damage to the heritage...
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An image fusion is a kind of single process which combines the necessary or efficient information from a set of different or similar input images into a single output image where the resulting image is more accurate, ...
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Industry 4.0 is the ongoing automation of conventional manufacturing and industrial applications using smart technology. Quality control (QC) is a set of procedures to ensure that a manufactured product adheres to a d...
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ISBN:
(纸本)9781665439947
Industry 4.0 is the ongoing automation of conventional manufacturing and industrial applications using smart technology. Quality control (QC) is a set of procedures to ensure that a manufactured product adheres to a defined set of quality criteria or meets the requirements of the customer. Many applications within the manufacturing domain employ image-processing or machine learning systems but deep learning-based applications are rare. The goal of this project is to leverage deep learning methods for the automation of quality control. A visual QC automation application is proposed that utilizes a camera placed over a product assembly line containing 3-D printed product samples in a smart factory prototype setup for data collection. After model training, the model will perform object detection and recognition for analyzing complex free-form products and perform product dimension and surface analysis to identify the products that meet the quality control guidelines.
Cellular microscopy is enhanced by computational paradigms such as imageprocessing, computer vision, and machine learning. image segmentation is vital for quantifying cell images, enabling tracking and subsequent app...
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In view of the demand for cigarette case appearance quality detection in the production process of cigarette enterprises, a machinevision-based method for detecting cigarette case appearance defects is proposed, and ...
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Research hotspots in food science and dental studies currently focus on analyzing food texture, preparing food boluses, and studying the interaction between food and the chewing system during the mastication process u...
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ISBN:
(纸本)9798350325621
Research hotspots in food science and dental studies currently focus on analyzing food texture, preparing food boluses, and studying the interaction between food and the chewing system during the mastication process using in vitro experiments. Several food repositioning mechanisms have been developed and applied to the chewing robots for different applications, but they are normally actively actuated by motors or pneumatic/hydraulic valves, which increase the complexity of the system. This study aims to develop a food repositioning mechanism to mimic the function of tongue and cheek muscles during food masticatory process with no actuation. The technical requirements of the new food repositioning mechanism are summarized by analyzing the pros and cons of the existing mechanisms. A new food repositioning mechanism based on spring and v-shaped inclined plates are developed, hinge structure is applied to support the inclined plates, and its performance is validated by using simulations.
Matrix-vector multiplication (MvM) operations play an important role in applications such as data processing and artificial neural networks. To meet the growing demand for computing power, the photonic MvM processor p...
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Matrix-vector multiplication (MvM) operations play an important role in applications such as data processing and artificial neural networks. To meet the growing demand for computing power, the photonic MvM processor provides what we believe to be a new computing architecture. In this paper, we propose a reconfigurable parallel MvM (RP-MvM) processor. To further improve the parallel computing dimension, wavelength division multiplexing (WDM) and digital subcarrier multiplexing (DSM) technologies were first incorporated into the photonic MvM. Compared with the traditional WDM-MvM architecture, the parallelism of RP-MvM scheme is increased by N times, where N is the carrier number of DSM signal. Moreover, the input data channel can be dynamically adjusted without changing the hardware scale, which improves the flexibility of computing system. The simulation results show that the RP-MvM scheme can achieve parallel computing operations of eight MvMs, with a computing speed of 128 GOPs. For a random 6-bit resolution data sequence, the root mean square error (RMSE) of calculation results is on the order of 1E-3. In addition, for the image edge extraction task based on Roberts operator, this scheme can realize the parallel processing of four grayscale images. Therefore, the proposed scheme provides an alternative approach for realizing a highly parallel and reconfigurable large-scale photonic MvM architecture.
BackgroundMonkeypox is a viral disease caused by the monkeypox virus (MPv). A surge in monkeypox infection has been reported since early May 2022, and the outbreak has been classified as a global health emergency as t...
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BackgroundMonkeypox is a viral disease caused by the monkeypox virus (MPv). A surge in monkeypox infection has been reported since early May 2022, and the outbreak has been classified as a global health emergency as the situation continues to worsen. Early and accurate detection of the disease is required to control its spread. machine learning methods offer fast and accurate detection of COvID-19 from chest X-rays, and chest computed tomography (CT) images. Likewise, computer vision techniques can automatically detect monkeypoxes from digital images, videos, and other *** this paper, we propose an automated monkeypox detection model as the first step toward controlling its global *** and methodA new dataset comprising 910 open-source images classified into five categories (healthy, monkeypox, chickenpox, smallpox, and zoster zona) was created. A new deep feature engineering architecture was proposed, which contained the following components: (i) multiple nested patch division, (ii) deep feature extraction, (iii) multiple feature selection by deploying neighborhood component analysis (NCA), Chi2, and ReliefF selectors, (iv) classification using SvM with 10-fold cross-validation, (v) voted results generation by deploying iterative hard majority voting (IHMv) and (vi) selection of the best vector by a greedy *** proposal attained a 91.87% classification accuracy on the collected dataset. This is the best result of our presented framework, which was automatically selected from 70 generated *** computed classification results and findings demonstrated that monkeypox could be successfully detected using our proposed automated model.
This paper presents a comparative study on the application of drone-assisted infrared thermography coupled with state-of-the-art machine learning models, including vision Transformers (viTs) and YOLOv8, for efficient ...
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The use of image acquisition, processing and recognition techniques already has a history in terms of practical applications. The current and future development of industrial applications favors the development of suc...
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ISBN:
(纸本)9781665484428
The use of image acquisition, processing and recognition techniques already has a history in terms of practical applications. The current and future development of industrial applications favors the development of such techniques based on increasing their performance. Considering this trend, it is necessary to adapt the contents of the artificial vision courses with an emphasis on the practical applicability with the high performance of the new methods and techniques in the field. At the Faculty of Automation, Computers and Electronics, from the University of Craiova, Romania, such a course is offered to students from the undergraduate programs in Multimedia Systems Engineering, Applied Electronics, and Mechatronics and Robotics, respectively. The course includes chapters dedicated to digital image acquisition, imageprocessing, image segmentation, image descriptors, image classification and recognition, and applications. This paper will present how to upgrade the chapter related to applications, referring to the practical application developed by a group of doctoral students from our faculty. Methodologies for the development of reliable and complex computer visionapplications which are used in a manufacturing environment are generally presented. The principles for the v-model development methodology and the Agile methodology are parts of this presentation. Students will receive the basic knowledge needed for comparing the advantages and disadvantages of these established methods in the manufacturing industry. In practice, these methods should measure the reliability of the system, what percentage of the functional requirements is achieved and at what quality, the behavior of the hardware and software components, and the behavior of the system when integrated into the plant environment. For validating the concept, the results obtained using the v-model and Agile methodologies into a computer vision automated inspection application for engine blocks from an automot
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