The internet of Vehicles (IoV) has brought a new era of innovation in transportation and mobility (T&M) in smart cities, made possible by the confluence of IoT and Machine Learning (ML) technology. The capabilitie...
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ISBN:
(纸本)9798350350661;9798350350654
The internet of Vehicles (IoV) has brought a new era of innovation in transportation and mobility (T&M) in smart cities, made possible by the confluence of IoT and Machine Learning (ML) technology. The capabilities and applications of the internet of Vehicles (IoV) have been greatly expanded by the increasing adoption of IoT, 5G connectivity, and autonomous vehicles. Modern machine learning (ML) approaches used in IoV service delivery are examined in this review paper, emphasizing how they might improve multimedia communication quality of experience (QoE) in vital industries like healthcare. ML-based service provisioning enhances the functionality and customer experience of the automotive sector by delivering tailored, efficient, and predictive services by analyzing data from connected automobiles.
Over the past several years, deep neural networks have permeated many fields of science research and have become an essential part of real-world applications. However, when the model encounters a test sample with unce...
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ISBN:
(纸本)9798350389913;9798350389906
Over the past several years, deep neural networks have permeated many fields of science research and have become an essential part of real-world applications. However, when the model encounters a test sample with uncertainty, compared with the distribution of the training set data, it is crucial for users to determine which of the model's predicted outputs for those test data are trustworthy and which are not, rather than being forced to give an untrustworthy prediction output. To this end, it is necessary to evaluate the model uncertainty, which enables to improve utilization of the model prediction results, especially some safety-critical systems. For image segmentation tasks of safety-critical systems, this paper proposes an uncertainty quantification method based on Gaussian processes to evaluate the trustworthiness of the output predicted by neural network models for the given input, so as to facilitate the selection and optimization of segmentation models and provide the model interpretability. The simulation results indicate that for the pixel error rate of each image, this method can give the confidence interval of the predicted output and the stability of the predicted output, achieving the objective of quantifying and understanding the confidence level of deep learning models.
Positron emission tomography (PET) is a commonly used medical imaging modality, but it has high noise at low doses. To further optimize PET image reconstruction, this paper proposes a novel approach that incorporates ...
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With the advancement of technology, the use of IoT technology for information management of safety production in chemical industrial parks is of great significance. This article designs an emergency rescue system for ...
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ISBN:
(纸本)9798350375084;9798350375077
With the advancement of technology, the use of IoT technology for information management of safety production in chemical industrial parks is of great significance. This article designs an emergency rescue system for chemical industrial parks based on the internet of Things, which mainly consists of a main control module, infrared detection module, image acquisition module, voice prompt module, network transmission module, etc. This system adopts Zigbee wireless networking technology, which has the characteristics of easy operation, low power consumption, low cost, easy expansion, and easy maintenance. Practice has shown that in the social environment of energy conservation and emission reduction, the system has high application value.
In recent years,it has been evident that internet is the most effective means of transmitting information in the form of documents,photographs,or videos around the *** purpose of an image compression method is to enco...
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In recent years,it has been evident that internet is the most effective means of transmitting information in the form of documents,photographs,or videos around the *** purpose of an image compression method is to encode a picture with fewer bits while retaining the decompressed image’s visual *** transmission,this massive data necessitates a lot of channel *** order to overcome this problem,an effective visual compression approach is required to resize this large amount of *** work is based on lossy image compression and is offered for static color *** quantization procedure determines the compressed data quality *** images are converted from RGB to international Commission on Illumination CIE La^(∗)b^(∗);and YCbCr color spaces before being *** the transform domain,the color planes are encoded using the proposed quantization *** improve the efficiency and quality of the compressed image,the standard quantization matrix is updated with the respective image *** used seven discrete orthogonal transforms,including five variations of the Complex Hadamard Transform,Discrete Fourier Transform and Discrete Cosine Transform,as well as thresholding,quantization,de-quantization and inverse discrete orthogonal transforms with CIE La^(∗)b^(∗);and YCbCr to RGB *** to signal noise ratio,signal to noise ratio,picture similarity index and compression ratio are all used to assess the quality of compressed *** the relevant transforms,the image size and bits per pixel are also *** the(n,n)block of transform,adaptive scanning is used to acquire the best feasible compression *** of these characteristics,multimedia systems and services have a wide range of possible applications.
This paper explores deep learning-based algorithms for electrocardiogram (ECG) signal processing and their applications in cardiac health monitoring. Initially, we provide an overview of the fundamental principles of ...
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Privacy violations are common in our technology-driven world, where almost everyone interacts with internet-connected electronic devices. To address this, cryptography has emerged, concealing data during transmission ...
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Passive bearing-crossing localization technology has an important application in the scenario of UAV (Unmanned Aerial Vehicle) target positioning, in which the removal of false intersection points in the process of mu...
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Nowadays, the advancement of modern communication systems, along with internet usability, enhances the application of multimedia data in various fields. In this context, security in multimedia data is highly demanding...
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ISBN:
(纸本)9789819780501;9789819780518
Nowadays, the advancement of modern communication systems, along with internet usability, enhances the application of multimedia data in various fields. In this context, security in multimedia data is highly demanding to prevent unauthorized access, as well as to ensure confidentiality. This paper introduces a new reversible blind imagewatermarking scheme to validate the image authentication and confidentiality for secret information. To address this aim, a spread-spectrum-based message hiding technique is developed. The reduced Lorenz map combined with the sine-cos map is employed here to produce a key-dependent pseudo-random number (PRN), which is directly mapped into the cover image according to the bit pattern of the secret message. On the other hand, the message hiding has been performed in the cover image by decomposing it using a two-level integer wavelet transform (IWT). The robustness of the scheme is further improved by employing Hamming (7, 4) code and a geometric distortion correction module. Several cover images are used to examine the effectiveness of the proposed scheme. The experimental results present that this approach has better or equivalent robustness against common sig-D nal processing distortions and geometric distortions compared to relevant existing schemes.
With the continuous advancement of internettechnology, the transmission and storage of medical images in the network environment are becoming increasingly frequent. Ensuring the security of these image data has becom...
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