In proposed system an automated attendance marking and management system is proposed by using face detection and recognition algorithms. Identification of human faces by the unique characteristics or features of their...
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In proposed system an automated attendance marking and management system is proposed by using face detection and recognition algorithms. Identification of human faces by the unique characteristics or features of their face is known as Face recognition. Currently, Face recognition technology is the fastest growing technology. Instead of using the traditional methods, this proposed system aims to develop an automated system that records the student's attendance by using facial recognition technology for those who are present during lecture hours. The main objective of this work is to make the attendance marking and management system fully automatic, simple and easy. In this work the facial recognition of face is done by imageprocessing techniques. The processed image is used to match with the existing stored record and then attendance is marked in the database correspondingly. Compared to existing system traditional attendance marking system, this system reduces the workload of people and also saves times. This proposed system is been implemented with 4 modules such as image Capturing, Segmentation of group photo and Face Detection, Face comparison and Recognition, Updating of Attendance in database.
This paper presents the computational modeling results of the rubber extrusion manufacturing process. The impact of the die swell phenomenon is quantified by running iterative models, differentiating the inflow rate. ...
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This paper presents the computational modeling results of the rubber extrusion manufacturing process. The impact of the die swell phenomenon is quantified by running iterative models, differentiating the inflow rate. The extrudate's dimensions are identified by making use of imageprocessingalgorithms for detecting the edge. Also, the velocity values at the outlet are calculated for various inflow rates and are presented graphically. The generated rules are correlating the manufacturing parameters with the Key Performance Indicators (KPIs) and can predict the extrudate's dimensions towards zero defect manufacturing. (C) 2018 The Authors. Published by Elsevier B.V.
The paper is dedicated to building big data processing methods and image classification using machine learning algorithms. Machine learning methods and their application to computer vision tasks, in particular to imag...
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Thyroid nodule is a common clinical condition. Ultrasound is usually used to make a preliminary diagnosis, because it is convenient and cheap. Therefore, the study of thyroid ultrasound images of thyroid nodules has i...
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ISBN:
(纸本)9783319942681;9783319942674
Thyroid nodule is a common clinical condition. Ultrasound is usually used to make a preliminary diagnosis, because it is convenient and cheap. Therefore, the study of thyroid ultrasound images of thyroid nodules has it's significance and value. This paper investigates the problem of locating thyroid nodules in ultrasound images by manual signs. The solution to this problem is divided into three parts: first, imageprocessing processes the image preliminary and find the approximate location of the signs;then, sign recognition recognize the signs accurately using CNN models;finally, boundary adjustment is used for the final adjustment of the border. Experimental results show that the algorithm proposed in this paper can accurately locate the nodules in thyroid ultrasound images.
The Automatic Number Plate Recognition (ANPR) is a imageprocessing innovation that utilizes the vehicle number (permit) plate for vehicle identification. The goal is to utilize the vehicle number plate to plan a prod...
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ISBN:
(数字)9781728112619
ISBN:
(纸本)9781728112626
The Automatic Number Plate Recognition (ANPR) is a imageprocessing innovation that utilizes the vehicle number (permit) plate for vehicle identification. The goal is to utilize the vehicle number plate to plan a productive programmed approved vehicle distinguishing proof framework. The framework is executed in the college entrance for security control. This paper highlights the license plate extraction algorithm where number plate is extracted using Sobel filter, morphological operations and Connected Component Analysis (CCA). Then character segmentation based on CCA and Spectral Analysis, then character recognition based on Support Vector Machine (SVM) technique. In OpenCV-Python, the proposed model is simulated and implemented and its performance is evaluated on the actual image.
The intruder's image and sound detection did not employ effetely in the various types of existing monitoring systems. The monitoring systems capture all wanted, unwanted objects in the monitoring zone, and do not ...
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ISBN:
(纸本)9781728102122
The intruder's image and sound detection did not employ effetely in the various types of existing monitoring systems. The monitoring systems capture all wanted, unwanted objects in the monitoring zone, and do not detect objects in the blind monitoring zone. Therefore, this paper aims to increase the accuracy of monitoring system by detecting only the desired object's image, sound or both accurately. The proposed system used the sound detection capability in order to increase the system accuracy. Different sound detection algorithms are used to detect the sound that obtained by various sensors, then Heron's law is implemented to avoid the sound from external sources and prevent to track the undesired objects. The obtained results increased the detection accuracy by 30% comparing to the existing systems results. The proposed system provides the ability to detect the desired intruder inside and outside monitoring zone and avoiding other small objects, which curtail the tracking errors rate by approximately 11%. The various sound detection algorithms implemented in the systems solve the problem of detecting the objects in the blind monitoring zone, where a location is not needed to track objects. Likewise, the Herons law is implemented to avoid the external source as well as to track the smaller object except for intruders.
We propose a novel learning strategy to train the optical neural networks based on neuroevolution. The accuracy of modulation formats recognition reach to 93%, indicating that the proposed method is competitive with o...
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ISBN:
(纸本)9781943580705
We propose a novel learning strategy to train the optical neural networks based on neuroevolution. The accuracy of modulation formats recognition reach to 93%, indicating that the proposed method is competitive with other learning algorithms.
Efficient query processing in spatial databases is of vital importance for numerous modern applications. In most cases, such processing is accomplished by taking advantage of spatial indexes. The xBR(+)-tree is an ind...
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ISBN:
(纸本)9783030008567;9783030008550
Efficient query processing in spatial databases is of vital importance for numerous modern applications. In most cases, such processing is accomplished by taking advantage of spatial indexes. The xBR(+)-tree is an index for point data which has been shown to outperform indexes belonging to the R-tree family. On the other hand, Solid-State Drives (SSDs) are secondary storage devices that exhibit higher (especially read) performance than Hard Disk Drives and nowadays are being used in database systems. Regarding query processing, the higher performance of SSDs is maximized when large sequences of queries (batch queries) are executed by exploiting the massive I/O advantages of SSDs. In this paper, we present algorithms for processing common spatial (point-location, window and distance-range) batch queries using xBR(+)-trees in SSDs. Moreover, utilizing small and large datasets, we experimentally study the performance of these new algorithms against processing of batch queries by repeatedly applying existing algorithms for these queries. Our experiments show that, even when the existing algorithms take advantage of LRU buffering that minimizes disk accesses, the new algorithms prevail performance-wise.
Keeping less valid data to obtain necessary information has become a new requirement in the signal-processing field. The paper employs adaptive dictionary for sparse representation, introduces a characteristic-weighti...
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ISBN:
(纸本)9781538660058
Keeping less valid data to obtain necessary information has become a new requirement in the signal-processing field. The paper employs adaptive dictionary for sparse representation, introduces a characteristic-weighting coefficient to offer detailed image information, and meanwhile performs Schmidt orthogonalization with the combination of Gaussian random measurement matrix to minimize the correlation of vectors in matrix. It raises the figure structural group sparse representation (FSGSR) algorithm based on matrix orthogonalization. Experiments indicate that this improved image reconstruction algorithm has enhanced the reconstructed image quality compared with typical algorithms during same time length.
Acute Lymphoblastic Leukemia (ALL) is the most prevalent acute leukemia in adults after Acute Myeloid Leukemia, with a diffusion of over 6500 persons per year just in the United States. In this research, we propose a ...
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ISBN:
(纸本)9781538611227
Acute Lymphoblastic Leukemia (ALL) is the most prevalent acute leukemia in adults after Acute Myeloid Leukemia, with a diffusion of over 6500 persons per year just in the United States. In this research, we propose a smart assistant determination method for ALL diagnosis using microscopic images. In this regard, K-means is employed to extract cell images after that wavelet transform is hired on cell images then statistical moments of the transformed image are computed to extract features. Afterward, a Chain Tabu search algorithm is proposed for feature selection of normal and abnormal cells to enable classifiers classifying ALL efficiently. Finally, Multi-Layer Perceptron (MLP) is used for classification. The proposed method is evaluated on ALL-IDB2. The proposed method achieved the accuracy of 98.88% and outperforms existed ALL diagnosis methods.
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