The personal computer is evolving from a purely personal device to one that can support multiple applications in different locations simultaneously. This paper describes how the connectivity and processing capability ...
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The personal computer is evolving from a purely personal device to one that can support multiple applications in different locations simultaneously. This paper describes how the connectivity and processing capability of the PC can be used in a distributed manner in the home to provide a variety of services like speech activated environmental command and control functions, digital video decoding, Internet telephony and entertainment control. As they are architected today, current PCs are challenged when trying to perform intensive signal processing tasks while managing several external connections (e.g. dial-up Internet) and multiple internal connections (e.g. cordless phone interface) at the same time. We describe some of these challenges, and what remains to be done to make the PC more capable in undertaking such a multifunctional challenge.
The growing number of applications for 3D graphics and imaging systems in the mass market requires the customized approach to the design of high-performance 3D graphics and imaging system architectures. That fact coup...
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The growing number of applications for 3D graphics and imaging systems in the mass market requires the customized approach to the design of high-performance 3D graphics and imaging system architectures. That fact coupled with the strong trends to industrial standardization of graphics API, such as OpenGL, leads to enhanced portability for imaging and graphics applications. The progress on the hardware support of API functionality gives a real possibility to use a top-down approach in the design of custom graphics/imaging systems based on the mixed hardware/software implementation of the OpenGL architecture. Software simulation is a relatively cheap and fast way for initial graphics architecture template development and evaluation to acquire the structure and parameters that can be used later for HDL elaboration and simulation. This paper discusses a 3D graphics and imaging system architecture model implementation based on OpenGL API hardware support simulation. The object-oriented approach has been used for this development of analytic and software models simulating hardware units on different stages of the graphics pipeline. The Interactive Imaging System architecture Composer has been developed in this project for fast run-time simulation management, data acquisition and interpretation. The expandable set of architecture templates uses a reconfigurable shared library of "virtual hardware units" simulating the different hardware structures for graphics and image processing.
Deep learning has been widely used for plant disease recognition in smart agriculture and has proven to be a powerful tool for image classification and pattern ***,it has limited interpretability for deep *** the tran...
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Deep learning has been widely used for plant disease recognition in smart agriculture and has proven to be a powerful tool for image classification and pattern ***,it has limited interpretability for deep *** the transfer of expert knowledge,handcrafted features provide a new way for personalized diagnosis of plant ***,irrelevant and redundant features lead to high *** this study,we proposed a swarm intelligence algorithm for feature selection[salp swarm algorithm for feature selection(SSAFS)]in image-based plant disease *** is employed to determine the ideal combination of handcrafted features to maximize classification success while minimizing the number of *** verify the effectiveness of the developed SSAFS algorithm,we conducted experimental studies using SSAFS and 5 metaheuristic *** evaluation metrics were used to evaluate and analyze the performance of these methods on 4 datasets from the UCI machine learning repository and 6 plant phenomics datasets from *** results and statistical analyses validated the outstanding performance of SSAFS compared to existing state-of-the-art algorithms,confirming the superiority of SSAFS in exploring the feature space and identifying the most valuable features for diseased plant image *** computational tool will allow us to explore an optimal combination of handcrafted features to improve plant disease recognition accuracy and processing time.
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