Conventional video coding methods have been developed based on the human visual system (HVS). However, in recent years, video has occupied a huge portion of internet traffic, and the mount of video data for machine co...
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ISBN:
(纸本)9781728198354
Conventional video coding methods have been developed based on the human visual system (HVS). However, in recent years, video has occupied a huge portion of internet traffic, and the mount of video data for machine consumption has increased rapidly due to the progress of neural networks. This paper proposes a novel machine-attention-based video coding method for machines. Inspired by the saliency-driven research, we first extract attention regions, sensitively affecting the machine vision performance, from the object detection network. Subsequently, a maximum a posterior (MAP)-based bit allocation method is applied to assign more bits to the attention regions. Our proposed method helps to maintain high machine vision performance whereas reducing the bitrate. Experimental results show that our proposed method achieves up to 34.89% bjontegaard delta (BD)-rate reduction for the video dataset and up to 44.70% BD-rate reduction for the image dataset compared to state-of-the-art video coding technology.
Intelligent connected vehicles (ICVs) refer to a new vehicle type that utilizes advanced information and communication technology to enable information exchange among vehicles, between vehicles and roads, and between ...
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With the development of the internet, social software and media have become ubiquitous, making images increasingly important in daily life. The dissemination of a large number of images on social networks has made inf...
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The manual identification of maize diseases is labor-intensive, requiring expertise and incurring substantial costs. Consequently, there is a pressing need for computer-based automated systems. Maize diseases not only...
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In this study, numerical simulation and analysis of leakage signal characteristics of gas pipelines with different leakage holes were carried out based on Fluent software. It was found that the differences in leakage ...
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Gait recognition technology, as a key branch in the field of identity recognition, has significant value but also faces challenges such as discomfort from wearable devices, the need for synchronized processing of gait...
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Perceptual image hashing is pivotal in various image processing applications, including image authentication, content-basedimage retrieval, tampered image detection, and copyright protection. This paper proposes a no...
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With the development of the internet and big data technology, massive amounts of data are transferred between different application systems and organizations, greatly increasing the difficulty of privacy protection an...
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ISBN:
(纸本)9798350386660;9798350386677
With the development of the internet and big data technology, massive amounts of data are transferred between different application systems and organizations, greatly increasing the difficulty of privacy protection and the risk of data leakage. Existing database fingerprinting schemes, while addressing the problem of traceability, are limited by the contradiction between the robustness of the fingerprints and the data distortion introduced by the embedding of fingerprints. They also struggle to protect sensitive data while maintaining data usability. To address such issues, this paper proposes a data leakage traceability scheme based on differential privacy and fingerprinting. This scheme processes the database using the Laplace mechanism for differential privacy, then treats the fingerprint information with the Arnold image transformation algorithm, and trains an approximate optimal key based on the fingerprint information using a genetic algorithm. This approach aims to enhance the robustness of the fingerprint scheme while reducing data distortion. Experimental results prove that this scheme has better robustness than existing fingerprint schemes after maintaining usability.
Denoising X-ray images is essential for improving medical image quality, especially in diagnosing conditions like knee osteoarthritis in Computer-Aided Diagnosis (CAD) systems. The presence of statistical noise, such ...
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Anomaly detection in internet of Things (IoT) systems is essential for preventing failures, security breaches, and inaccurate predictions. Deep learning-based approaches are effective for this purpose but often suffer...
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