Multi-image steganography ensures privacy protection while avoiding suspicion from third parties by embedding multiple secret images within a cover image. However, existing multi-image steganographic methods fail to m...
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Vehicular ad hoc networks (VANETs) have emerged as a key area of interest in the research community due to their wide range of applications. As the number of vehicles increases, VANETs encounter challenges with access...
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In high-energy physics experiments, the precise reconstruction of the transverse momentum of jets is challenging. The primary obstacle is the interference caused by background noise particles overlapping with the jet ...
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Searchable encryption, also known as secure search, is a technology that enables search operations on encrypted data while maintaining its confidentiality. Extensive research has been conducted on searchable encryptio...
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Physical layer authentication(PLA)in the context of the Internet of Things(IoT)has gained significant *** with traditional encryption and blockchain technologies,PLA provides a more computationally efficient alternati...
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Physical layer authentication(PLA)in the context of the Internet of Things(IoT)has gained significant *** with traditional encryption and blockchain technologies,PLA provides a more computationally efficient alternative to exploiting the properties of the wireless medium *** existing PLA solutions rely on static mechanisms,which are insufficient to address the authentication challenges in fifth generation(5G)and beyond wireless ***,with the massive increase in mobile device access,the communication security of the IoT is vulnerable to spoofing *** overcome the above challenges,this paper proposes a lightweight deep convolutional neural network(CNN)equipped with squeeze and excitation module(SE module)in dynamic wireless environments,namely *** be more specific,a convolution factorization is developed to reduce the complexity of PLA models based on deep ***,an SE module is designed in the deep CNN to enhance useful features andmaximize authentication *** with the existing solutions,the proposed SE-ConvNet enabled PLA scheme performs excellently in mobile and time-varying wireless environments while maintaining lower computational complexity.
The Internet ofThings(IoT)and edge computing have substantially contributed to the development and growth of smart *** handled time-constrained services and mobile devices to capture the observing environment for surv...
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The Internet ofThings(IoT)and edge computing have substantially contributed to the development and growth of smart *** handled time-constrained services and mobile devices to capture the observing environment for surveillance *** systems are composed of wireless cameras,digital devices,and tiny sensors to facilitate the operations of crucial healthcare ***,many interactive applications have been proposed,including integrating intelligent systems to handle data processing and enable dynamic communication functionalities for crucial IoT ***,most solutions lack optimizing relayingmethods and impose excessive overheads for maintaining devices’***,data integrity and trust are another vital consideration for nextgeneration *** research proposed a load-balanced trusted surveillance routing model with collaborative decisions at network edges to enhance energymanagement and resource *** leverages graph-based optimization to enable reliable analysis of decision-making ***,mobile devices integratewith the proposed model to sustain trusted routes with lightweight privacy-preserving and *** proposed model analyzed its performance results in a simulation-based environment and illustrated an exceptional improvement in packet loss ratio,energy consumption,detection anomaly,and blockchain overhead than related solutions.
Escape routing is a critical task in the design of printed circuit boards (PCB) and integrated circuits (IC), aiming to establish effective connections among multiple pin points while avoiding path overlaps and interf...
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Accurate brain tumor classification is crucial for precise diagnosis and effective treatment planning. Despite the extensive use of comparative analyses of deep learning models in the literature, no prior studies have...
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Recommendation engines leverage past user preferences to forecast their future interests. Many deep learning-based recommendation systems aim to explore the intricate dynamics between users and particular items. Typic...
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The objective of image-based virtual try-on is to seamlessly integrate clothing onto a target image, generating a realistic representation of the character in the specified attire. However, existing virtual try-on met...
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The objective of image-based virtual try-on is to seamlessly integrate clothing onto a target image, generating a realistic representation of the character in the specified attire. However, existing virtual try-on methods frequently encounter challenges, including misalignment between the body and clothing, noticeable artifacts, and the loss of intricate garment details. To overcome these challenges, we introduce a two-stage high-resolution virtual try-on framework that integrates an attention mechanism, comprising a garment warping stage and an image generation stage. During the garment warping stage, we incorporate a channel attention mechanism to effectively retain the critical features of the garment, addressing challenges such as the loss of patterns, colors, and other essential details commonly observed in virtual try-on images produced by existing methods. During the image generation stage, with the aim of maximizing the utilization of the information proffered by the input image, the input features undergo double sampling within the normalization procedure, thereby enhancing the detail fidelity and clothing alignment efficacy of the output image. Experimental evaluations conducted on high-resolution datasets validate the effectiveness of the proposed method. Results demonstrate significant improvements in preserving garment details, reducing artifacts, and achieving superior alignment between the clothing and body compared to baseline methods, establishing its advantage in generating realistic and high-quality virtual try-on images.
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