In recent years, infrared target detection has played a crucial role in intelligent transportation and assisted driving. Addressing the current issues of low detection accuracy, poor robustness, and missed detections ...
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We propose a deep learning model for Chinese dialect speech recognition based on key vector de-optimization of temporal features. Unlike traditional Hidden Markov Models (HMMs) and their variants, the model uses stack...
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This paper proposed a new algorithm in the end-to-end automatic speech recognition. For the end-to-end speech recognition model, we select greedy soup instead of the average model parameters in WeNet. We proposed a dy...
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With the advent of the information security era,it is necessary to guarantee the privacy,accuracy,and dependable transfer of *** study presents a new approach to the encryption and compression of color *** is predicat...
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With the advent of the information security era,it is necessary to guarantee the privacy,accuracy,and dependable transfer of *** study presents a new approach to the encryption and compression of color *** is predicated on 2D compressed sensing(CS)and the hyperchaotic ***,an optimized Arnold scrambling algorithm is applied to the initial color images to ensure strong ***,the processed images are con-currently encrypted and compressed using 2D *** them,chaotic sequences replace traditional random measurement matrices to increase the system’s ***,the processed images are re-encrypted using a combination of permutation and diffusion *** addition,the 2D projected gradient with an embedding decryption(2DPG-ED)algorithm is used to reconstruct *** with the traditional reconstruction algorithm,the 2DPG-ED algorithm can improve security and reduce computational ***,it has better *** experimental outcome and the performance analysis indicate that this algorithm can withstand malicious attacks and prove the method is effective.
Missing values pose a formidable obstacle in multivariate time series analysis. Existing imputation methods rely on entangled representations that struggle to simultaneously capture multiple orthogonal time-series pat...
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Content Aiming at the problem that iris images are easily affected by eyelid and eyelash noise, which leads to low positioning accuracy and poor stability, an iris positioning network based on YOLOv4 model is proposed...
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Complex networks are becoming more complex because of the use of many components with diverse technologies. In fact, manual configuration that makes each component interoperable has breed latent danger to system secur...
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Complex networks are becoming more complex because of the use of many components with diverse technologies. In fact, manual configuration that makes each component interoperable has breed latent danger to system security. There is still no comprehensive review of these studies and prospects for further research. According to the complexity of component configuration and difficulty of security assurance in typical complex networks, this paper systematically reviews the abstract models and formal analysis methods required for intelligent configuration of complex networks, specifically analyzes, and compares the current key technologies such as configuration semantic awareness, automatic generation of security configuration, dynamic deployment, and verification evaluation. These technologies can effectively improve the security of complex networks intelligent configuration and reduce the complexity of operation and maintenance. This paper also summarizes the mainstream construction methods of complex networks configuration and its security test environment and detection index system, which lays a theoretical foundation for the formation of the comprehensive effectiveness verification capability of configuration security. The whole lifecycle management system of configuration security process proposed in this paper provides an important technical reference for reducing the complexity of network operation and maintenance and improving network security.
The traditional Monte Carlo rendering method accurately renders 3D scenes but suffers from slow rendering speeds, limiting its suitability for high frame rate applications. Light probes offer a solution for achieving ...
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Removing clouds from remote sensing images poses a significant challenge in image analysis. Despite the widespread application of deep learning methods in the field of cloud removal, their ability to extract and integ...
The triangle mesh model with huge volume is not conducive to computer storage, analysis and rendering, and the mesh simplification method can effectively reduce the complexity of the triangle mesh model, but there are...
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