Pixel-level structure segmentations have attracted considerable attention,playing a crucial role in autonomous driving within the metaverse and enhancing comprehension in light field-based machine ***,current light fi...
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Pixel-level structure segmentations have attracted considerable attention,playing a crucial role in autonomous driving within the metaverse and enhancing comprehension in light field-based machine ***,current light field modeling methods fail to integrate appearance and geometric structural information into a coherent semantic space,thereby limiting the capability of light field transmission for visual *** this paper,we propose a general light field modeling method for pixel-level structure segmentation,comprising a generative light field prompting encoder(LF-GPE)and a prompt-based masked light field pretraining(LF-PMP)*** LF-GPE,serving as a light field backbone,can extract both appearance and geometric structural cues *** aligns these features into a unified visual space,facilitating semantic ***,our LF-PMP,during the pretraining phase,integrates a mixed light field and a multi-view light field *** prioritizes considering the geometric structural properties of the light field,enabling the light field backbone to accumulate a wealth of prior *** evaluate our pretrained LF-GPE on two downstream tasks:light field salient object detection and semantic *** results demonstrate that LF-GPE can effectively learn high-quality light field features and achieve highly competitive performance in pixel-level segmentation tasks.
Small-state stream ciphers (SSCs) idea is based on using key bits not only in the initialization but also continuously in the keystream generation phase. A time-memory-data tradeoff (TMDTO) distinguishing attack was s...
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Small-state stream ciphers (SSCs) idea is based on using key bits not only in the initialization but also continuously in the keystream generation phase. A time-memory-data tradeoff (TMDTO) distinguishing attack was successfully applied against all SSCs in 2017 by Hamann et al. They suggested using not only key bits but also initial value (IV) bits continuously in the keystream generation phase to strengthen SSCs against TMDTO attacks. Then, Hamann and Krause proposed a construction based on using only IV bits continuously in the packet mode. They suggested an instantiation of an SSC and claimed that it is resistant to TMDTO attacks. We point out that accessing IV bits imposes an overhead on cryptosystems that might be unacceptable in some applications. More importantly, we show that the proposed SSC remains vulnerable to TMDTO attacks 1. To resolve this security threat, the current paper proposes constructions based on storing key or IV bits that are the first to provide full security against TMDTO attacks. Five constructions are proposed for different applications by considering efficiency. Designers can obtain each construction’s minimum volatile state length according to the desirable keystream, key and IV lengths.
Learning causal structures from observational data is critical for causal discovery and many machine learning tasks. Traditional constraint-based methods first adopt conditional independence (CI) tests to learn a glob...
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The adversarial wiretap channel of type II (AWTC-II) is a communication channel that can a) read a fraction of the transmitted symbols up to a given bound and b) induce both errors and erasures in a fraction of the sy...
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In the growing information retrieval (IR) world, selecting suitable keywords and generating queries is important for effective retrieval. Modern database applications need a sophisticated interface for automatically u...
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The Internet of Things(loT)has grown rapidly due to artificial intelligence driven edge *** enabling many new functions,edge computing devices expand the vulnerability surface and have become the target of malware ***...
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The Internet of Things(loT)has grown rapidly due to artificial intelligence driven edge *** enabling many new functions,edge computing devices expand the vulnerability surface and have become the target of malware ***,attackers have used advanced techniques to evade defenses by transforming their malware into functionality-preserving *** systematically analyze such evasion attacks and conduct a large-scale empirical study in this paper to evaluate their impact on *** specifically,we focus on two forms of evasion attacks:obfuscation and adversarial *** the best of our knowledge,this paper is the first to investigate and contrast the two families of evasion attacks *** apply 10 obfuscation attacks and 9 adversarial attacks to 2870 malware *** obtained findings are as follows.(1)Commercial Off-The-Shelf(COTS)malware detectors are vulnerable to evasion attacks.(2)Adversarial attacks affect COTS malware detectors slightly more effectively than obfuscated malware examples.(3)Code similarity detection approaches can be affected by obfuscated examples and are barely affected by adversarial attacks.(4)These attacks can preserve the functionality of original malware examples.
Electroencephalogram (EEG) reveals the brain dynamics that are of a great value in clinical applications, e.g., epilepsy diagnosis, cognitive status, and other disorders. Intracranial Electroencephalogram (iEEG) is en...
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Scattering medium in light path will cause distortion of the light field,resulting in poor signal-to-noise ratio(SNR)of ghost *** disturbance is usually eliminated by the method of *** deduce the intensity fluctuation...
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Scattering medium in light path will cause distortion of the light field,resulting in poor signal-to-noise ratio(SNR)of ghost *** disturbance is usually eliminated by the method of *** deduce the intensity fluctuation correlation function of the ghost imaging with the disturbance of the scattering medium,which proves that the ghost image consists of two correlated results:the image of scattering medium and the target *** effect of the scattering medium can be eliminated by subtracting the correlated result between the light field after the scattering medium and the reference light from ghost image,which verifies the theoretical *** research may provide a new idea of ghost imaging in harsh environment.
Predicting students’academic achievements is an essential issue in education,which can benefit many stakeholders,for instance,students,teachers,managers,*** with online courses such asMOOCs,students’academicrelatedd...
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Predicting students’academic achievements is an essential issue in education,which can benefit many stakeholders,for instance,students,teachers,managers,*** with online courses such asMOOCs,students’academicrelateddata in the face-to-face physical teaching environment is usually sparsity,and the sample size is *** makes building models to predict students’performance accurately in such an environment even *** paper proposes a Two-WayNeuralNetwork(TWNN)model based on the bidirectional recurrentneural network and graph neural network to predict students’next semester’s course performance using only theirprevious course *** experiments on a real dataset show that our model performs better thanthe baselines in many indicators.
Recently,we demonstrated the success of a time-synchronized state estimator using deep neural networks(DNNs)for real-time unobservable distribution *** this paper,we provide analytical bounds on the performance of the...
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Recently,we demonstrated the success of a time-synchronized state estimator using deep neural networks(DNNs)for real-time unobservable distribution *** this paper,we provide analytical bounds on the performance of the state estimator as a function of perturbations in the input *** has already been shown that evaluating performance based only on the test dataset might not effectively indicate the ability of a trained DNN to handle input *** such,we analytically verify the robustness and trustworthiness of DNNs to input perturbations by treating them as mixed-integer linear programming(MILP)*** ability of batch normalization in addressing the scalability limitations of the MILP formulation is also *** framework is validated by performing time-synchronized distribution system state estimation for a modified IEEE 34-node system and a real-world large distribution system,both of which are incompletely observed by micro-phasor measurement units.
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