The world economy is threatened by counterfeit currencies. Counterfeit currencies are often difficult, time-consuming and ineffective to identify manually. Automated methods based on imageprocessing techniques and ma...
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China has seen an unheard-of surge in interest in deep-learning methods for image restoration in recent years. Most of these strategies draw inspiration from the established variational technique and related optimizat...
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The paper presents a novel approach to describing the elements of technical system structures, which offers new avenues for enhancing the automation of this information processing. This facilitates improving the condi...
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The paper presents a novel approach to describing the elements of technical system structures, which offers new avenues for enhancing the automation of this information processing. This facilitates improving the conditions for the initial stages of technical systems' development, which pertain to synthesizing their structures and schemes and are currently conducted exclusively by humans. The paper proposes a methodology for forming a digital description of the characteristics of structural elements that can be combined into a single structure of a specific technical system. This description is based on creating a multidimensional vector, which can be further processed using appropriate mathematical tools. This provides the possibility of processing this information by using mathematics. A methodology for forming vectors of description of structural elements of technical systems is proposed following the requirements for their effective use in algorithms implemented by computer programming. The presented approach establishes the foundation for the development of mathematical algorithms for processes related to the creation of technical system structures, their classification, efficient storage in the form of a database, efficient search by a large number of features, and other related tasks.
This paper aims to review and synthesize recent work on emotion recognition systems based on facial expressions, combined with neurological (EEG) and cardiac (ECG) signals. Above all, it explores the different methods...
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In the information age, imageprocessing technology has become prevalent across various domains. To enhance image correction, computer vision algorithms can be employed. Traditional methods for structural system ident...
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In machine/computer vision, cameras serve a major role in image acquisition. Surveillance scenarios typically rely on Closed-Circuit Television (CCTV) cameras. This study aims to evaluate industrial cameras within a s...
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ISBN:
(纸本)9798350350494;9798350350500
In machine/computer vision, cameras serve a major role in image acquisition. Surveillance scenarios typically rely on Closed-Circuit Television (CCTV) cameras. This study aims to evaluate industrial cameras within a surveillance application, contrasting their performance with that of CCTV cameras. We explore the comparative analysis of CCTV and industrial cameras for vehicle attribute recognition, specifically concentrating on the recognition of vehicle color and model using deep learning techniques. To train and evaluate the models, we have created datasets from images captured by both a CCTV and an industrial camera. Our findings indicate that the industrial camera outperforms the CCTV. However, employing advanced processingalgorithms has the potential to minimize the performance gap between these two cameras. Our research represents one of the initial comparative analyses between these camera types, offering valuable guidance in selecting the most suitable camera for specific applications.
The implementation of data compression in embedded platforms and portable systems is growing rapidly due to the demands for image and video processing in daily human life. Among the data compression applications, medi...
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ISBN:
(纸本)9798350371635;9798350371628
The implementation of data compression in embedded platforms and portable systems is growing rapidly due to the demands for image and video processing in daily human life. Among the data compression applications, medical imaging, such as Computed Tomography (CT), and Light Detection And Ranging (LiDAR) have become active research areas, especially when data transmissions must be performed over a communication interface. Because of the complexity of data compression algorithms and the high resolution of input streams, current embedded platforms may not be able to fully exploit data compression algorithms. To address this restriction, recent approaches utilize hardware accelerators to speed up the computation. Among available hardware accelerators, system-on-a-chip field-programmable gate arrays (SoC-FPGAs) have emerged as an important architecture approach in terms of achieving satisfactory computational performances. This study presents a hardware accelerator for the computation of a differential pulse code modulation (DPCM) algorithm implemented and synthesized on a Zynq SoC-FPGA and achieving an acceleration factor of 88x.
作者：
Yi, WangSchool of Law
Shandong University of Technology Economic Law Shandong Zibo255000 China
This research focuses on constructing an efficient imageprocessing model, which is rooted in computer vision algorithms, to ameliorate image distortion and optimize visual display systems. The article initially discu...
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Soil type identification stands as a crucial concern in numerous countries, to ensure optimal crop yield, farmers need to accurately identify the suitable soil type for specific crops, which plays a significant role i...
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ISBN:
(纸本)9789819720811;9789819720828
Soil type identification stands as a crucial concern in numerous countries, to ensure optimal crop yield, farmers need to accurately identify the suitable soil type for specific crops, which plays a significant role in meeting the heightened global food demand. The objective of this survey paper is to present a thorough and up-to-date overview of prevailing methodologies in soil identification, primarily focusing on image analysis, machine learning, and deep learning techniques. The paper initiates by highlighting the significance of soil identification and the limitations inherent in traditional methods. It then delves into the fundamental principles of imageprocessing, deep learning, and spectroscopy, explaining how these techniques can be applied to soil identification. The survey presents an in-depth analysis of various imageprocessing techniques employed for soil identification, including image segmentation, feature extraction, and classification algorithms. Furthermore, it discusses the application of deep learning models for soil classification based on image data.
We present a quantum inspired image augmentation protocol which is applicable to classical images and, in principle, due to its known quantum formulation applicable to quantum systems and quantum machine learning in t...
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ISBN:
(纸本)9798350344868;9798350344851
We present a quantum inspired image augmentation protocol which is applicable to classical images and, in principle, due to its known quantum formulation applicable to quantum systems and quantum machine learning in the future. The augmentation technique relies on the phenomenon Anderson localization. As we will illustrate by numerical examples the technique changes classical wave properties by interference effects resulting from scatterings at impurities in the material. We explain that the augmentation can be understood as multiplicative noise, which counter-intuitively averages out, by sampling over disorder realizations. Furthermore, we show how the augmentation can be implemented in arrays of disordered waveguides with direct implications for an efficient optical image transfer.
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