Mobile Internet Protocol v6 (MIPv6) is a protocol that allows a mobile node (MN) to transparently maintain connections while moving from one subnet to another. Using the route optimization (RO) method in MIPv6 gives o...
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Testing autonomous vehicles (AVs) under various environmental scenarios that lead the vehicles to unsafe situations is known to be challenging. Given the infinite possible environmental scenarios, it is essential to f...
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In most E-learning systems, educational activities are presented in a static way without bearing in mind the particulars or student levels and skills. Personalization and adaptation of an E-learning management system ...
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Hyperspectral image super resolution aims to improve the spatial resolution of given hyperspectral images, which has become a highly attractive topic in the field of image processing. Existing techniques typically foc...
Hyperspectral image super resolution aims to improve the spatial resolution of given hyperspectral images, which has become a highly attractive topic in the field of image processing. Existing techniques typically focus on super resolution with sufficient training data. However, restricted by data acquisition conditions, certain hyperspectral images or band images are very different to obtain, resulted in insufficient training data. In order to solve this problem, a new hyperspectral image super resolution method is proposed in this paper in an effort to conduct the super resolution task over insufficient (sparse) training data, by applying the recently introduced ANFIS (Adaptive Network-based Fuzzy Inference System) interpolation method. Particularly, the training dataset is divided into several subsets. For the subsets with sufficient training data, the relevant ANFIS models are trained using standard ANFIS learning algorithm, while for the subsets with sparse training data, the corresponding ANFIS models are interpolated through the use of ANFIS interpolation. Experimental results indicate that compared with the methods using sufficient training data, the proposed method can achieve very similar result, showing its effectiveness for situations where only sparse training data is available.
Literature reviews play a crucial role in scientific research for understanding the current state of research, identifying gaps, and guiding future studies on specific topics. However, the process of conducting a comp...
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Affine correspondences have traditionally been used to improve feature matching over wide baselines. While recent work has successfully used affine correspondences to solve various relative camera pose estimation prob...
Affine correspondences have traditionally been used to improve feature matching over wide baselines. While recent work has successfully used affine correspondences to solve various relative camera pose estimation problems, less attention has been given to their use in absolute pose estimation. We introduce the first general solution to the problem of estimating the pose of a calibrated camera given a single observation of an oriented point and an affine correspondence. The advantage of our approach (P1AC) is that it requires only a single correspondence, in comparison to the traditional point-based approach (P3P), significantly reducing the combinatorics in robust estimation. P1AC provides a general solution that removes restrictive assumptions made in prior work and is applicable to large-scale image-based localization. We propose a minimal solution to the P1AC problem and evaluate our novel solver on synthetic data, showing its numerical stability and performance under various types of noise. On standard image-based localization benchmarks we show that P1AC achieves more accurate results than the widely used P3P algorithm. Code for our method is available at https://***/jonathanventura/P1AC/.
Masks have remained an important mitigation strategy in the fight against COVID-19 due to their ability to prevent the transmission of respiratory droplets between individuals. In this work, we provide a comprehensive...
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Masks have remained an important mitigation strategy in the fight against COVID-19 due to their ability to prevent the transmission of respiratory droplets between individuals. In this work, we provide a comprehensive quantitative analysis of the impact of mask-wearing. To this end, we propose a novel agent-based model of viral spread on networks where agents may either wear no mask or wear one of several types of masks with different properties (e.g., cloth or surgical). We derive analytical expressions for three key epidemiological quantities: The probability of emergence, the epidemic threshold, and the expected epidemic size. In particular, we show how the aforementioned quantities depend on the structure of the contact network, viral transmission dynamics, and the distribution of the different types of masks within the population. Through extensive simulations, we then investigate the impact of different allocations of masks within the population and tradeoffs between the outward efficiency and inward efficiency of the masks. Interestingly, we find that masks with high outward efficiency and low inward efficiency are most useful for controlling the spread in the early stages of an epidemic, while masks with high inward efficiency but low outward efficiency are most useful in reducing the size of an already large spread. Last, we study whether degree-based mask allocation is more effective in reducing the probability of epidemic as well as epidemic size compared to random allocation. The result echoes the previous findings that mitigation strategies should differ based on the stage of the spreading process, focusing on source control before the epidemic emerges and on self-protection after the emergence.
Transmission line defect recognition models have traditionally used general pre-trained weights as the initial basis for their training. These models often suffer weak generalization capability due to the lack of doma...
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As an extension of the traditional encryption technology,information hiding has been increasingly used in the fields of communication and network media,and the covert communication technology has gradually *** blockch...
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As an extension of the traditional encryption technology,information hiding has been increasingly used in the fields of communication and network media,and the covert communication technology has gradually *** blockchain technology that has emerged in recent years has the characteristics of decentralization and tamper resistance,which can effectively alleviate the disadvantages and problems of traditional covert ***,its combination with covert communication thus far has been mostly at the theoretical *** BLOCCE method,as an early result of the combination of blockchain and covert communication technology,has the problems of low information embedding efficiency,the use of too many Bitcoin addresses,low communication efficiency,and high *** present research improved on this method,designed the V-BLOCCE which uses base58 to encrypt the plaintext and reuses the addresses generated by Vanitygen multiple times to embed *** greatly improves the efficiency of information embedding and decreases the number of Bitcoin addresses *** the premise of ensuring the order,the Bitcoin transaction OP_RETURN field is used to store the information required to restore the plaintext and the transactions are issued at the same time to improve the information transmission ***,a more efficient and feasible method for the application of covert communication on the blockchain is *** addition,this paper also provides a more feasible scheme and theoretical support for covert communication in blockchain.
Internet of things (IoT) encompasses millions of resource constrained wirelessly connected devices that are very often prone to external malicious attacks. Hence, there arises a need for protecting these devices from ...
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