Preclinical research, clinical diagnosis, and treatment can all benefit from the information that a medical image can offer. Due to the increased usage of digital medical imaging, numerous researchers are actively cre...
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We propose the development of an Adaptive Vehicle Control (AVC) system using readily available components such as a Raspberry Pi microcontroller, a motor, a motor driver, and a Raspberry Pi camera. This system aims to...
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There are many challenges for a Deep Learning application project. Many problems need to be solved in an optimal way to improve the performance of the system. We can focus on a specific step or on the whole process. T...
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The phase information of multi-source hybrid images is prone to confusion during image propagation. Since traditional phase retrieval algorithms require a large number of assumptions that cannot be executed by obtaini...
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In country such as India due to monsoon and frequent climatic changes leads to natural disasters such as floods, drought, landslides, cyclones, forest fire, earthquake and so on. The post disaster badly impacts on hum...
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image segmentation in imageprocessing is the method by which images are divided into different segments. Many methods are available and one of the commonly used method are fuzzy-based systems. This paper ignites ligh...
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The paper presents a comparative analysis of nature inspired Artificial Bee Colony and Particle Swarm Optimization algorithms for the enhancement of images. The paper briefly reviews the swarm-based algorithms. It des...
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ISBN:
(纸本)9781665424615
The paper presents a comparative analysis of nature inspired Artificial Bee Colony and Particle Swarm Optimization algorithms for the enhancement of images. The paper briefly reviews the swarm-based algorithms. It describes the dynamics of ABC and Particle Swarm Optimization algorithm and mapping for image enhancement. The key purpose of imageprocessing is to extract essential features from images. During an imageprocessing operation, the input given is an image, and its output is an enhanced high-quality image based on some characteristics/features related to that image. The mapping of the ABC and PSO algorithms for image enhancement was implemented using the Matlab imageprocessing toolbox. For both algorithms ABC and PSO, the parameters of Contrast Enhancement alpha was set in the range of 0-255 and beta was set in the range of 1-109. Finally, the Comparative Analysis of ABC and PSO algorithms was done using the metrics of Entropy, MSE and PSNR values for the images. It is found that ABC yields a better performance as compared to PSO.
Visual informations is very rich to control and pursue mobile robots, like wheeled mobile robots, underwater robots and aerospace mobile robots, etc. These are considered as mobile robots that move in different spaces...
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ISBN:
(纸本)9781665427357
Visual informations is very rich to control and pursue mobile robots, like wheeled mobile robots, underwater robots and aerospace mobile robots, etc. These are considered as mobile robots that move in different spaces, their main problem in this case is navigation especially in unknown environments. In effect, this navigation is possible only by the localisation and orientation of the robot by using different embedded sensors. We have the camera which is a necessary sensor in this work, it is an embedded instrument that gives very rich visual information as a sensor complementing the other sensors. In this context, the recognition of objects from visual informations is a main function among the functions very useful in imageprocessing tasks due to its varied applications in the field of robotics. Based on the analysis of this informations and the determination of image features like color or shape or object primitives (points, lines, edges, etc.) or some other features. What interest us in this paper, various feature extraction techniques and classification of point and edge detection are discussed which are required for object recognition showing advantages and disadvantages of the selected algorithms. So, points and edge detection refers to the process of identifying and detecting sharp discontinuities in an image. In this work, we try to develop a novel algorithm using the work on the existing to create a novel detector.
Multimodal biometric systems unite data from multiple biometric sources to surmount the limitations of individual systems. This paper presents an efficient algorithm for extracting details based on the image represent...
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ISBN:
(数字)9798350309249
ISBN:
(纸本)9798350309256
Multimodal biometric systems unite data from multiple biometric sources to surmount the limitations of individual systems. This paper presents an efficient algorithm for extracting details based on the image representation of fingerprints. Additionally, we conduct an in-depth investigation of T-Norm algorithms and offer a comprehensive score-level merging analysis. This analysis combines matching outcomes derived from the left and right fingerprints using the Hammacher, Schweizer-Sklar, Dombi, and Yager algorithms. The latter approaches are compared based on the receiver operating characteristic curve. The experimental evaluation conducted on the NIST fingerprint database validates the efficacy of fusion at the score level. Furthermore, it demonstrates the effectiveness of the proposed algorithm when compared to other T-Norms.
In recent years, with the development of science and technology and its application in agricultural production, China's agricultural science and technology have made great progress, the concept of "agricultur...
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ISBN:
(数字)9781665454575
ISBN:
(纸本)9781665454575
In recent years, with the development of science and technology and its application in agricultural production, China's agricultural science and technology have made great progress, the concept of "agricultural processing"has been mentioned, and the research on agricultural processing has also achieved fruitful results. The combination of intelligent and automated machine learning algorithms with traditional industries can promote productivity improvement on the one hand, and realize industrial upgrading and transformation on the other hand. However, in practical production applications, machine learning algorithms are restricted by factors such as high cost, and the research and application of machine learning algorithms are greatly limited. With the development of virtual simulation technology in the field of machine learning algorithm research, it provides a new way for machine learning algorithm technology to be applied to agricultural product processing. Therefore, the research on machine learning algorithms has become a trend. The development of machine learning algorithms will drive the development of modern agriculture. It is very necessary for the research of machine learning algorithms to learn algorithms. The image is converted into a data matrix, and a computer used to replace the human brain is used to analyze the image, while completing a vision related task. China's agricultural development is facing severe challenges such as rising costs, continuous deterioration of the ecological environment and high tension of resource conditions. With the deepening of machine learning algorithm research and the rapid development of machine learning algorithm technology, machine learning algorithm simulation technology, as a safe and economic experimental tool in the application of machine learning algorithm technology, plays a more and more important role. In order to make full use of the latest research results abroad and narrow the gap with the advanced level ab
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