Recent transformers-based systems are advancing image captioning applications. However, those works have been mainly applied to English-based image captioning problems. In this paper, we introduce a transformers-based...
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ISBN:
(纸本)9798350343557
Recent transformers-based systems are advancing image captioning applications. However, those works have been mainly applied to English-based image captioning problems. In this paper, we introduce a transformers-based Turkish-based image captioning algorithm. Our proposed algorithm uses appearance and geometry features from the input image and combines them along with the WordPiece embeddings to generate the Turkish-based caption. Our experimental results show improvement when compared to the other existing techniques including the original ORT and the show-and-tell algorithms.
This paper presents an innovative approach to automatic volume control using imageprocessing and deep learning techniques. The ability to automatically adjust volume levels based on environmental factors and user pre...
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This paper presents an innovative way of image compression using Field-Programmable Gate Array (FPGA) implementation of the Integer Wavelet Transform (IWT) and Discrete Wavelet Transform (DWT) algorithms. For situatio...
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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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Computational methods are nowadays ubiquitous in the field of bioinformatics and biomedicine. Besides established fields like molecular dynamics, genomics or neuroimaging, new emerging methods rely heavily on large sc...
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Computational methods are nowadays ubiquitous in the field of bioinformatics and biomedicine. Besides established fields like molecular dynamics, genomics or neuroimaging, new emerging methods rely heavily on large scale computational resources to manage Terabytes or Petabytes of data and TeraFlops or PetaFlops of computing power for simulating highly complex models, or many-task processes and workflows for processing and analysing *** special issue contains papers presenting novel aspects of security and performance in infrastructures used for applications in the Life Sciences, optimizations for popular applications, such as genomics and pandemic modelling, and contributions related to new algorithms joining machine learning and data processing platforms to increase the efficiency and accuracy of bioinformatics.
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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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.
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