Data Cloud Storage is a service that allows data to save data on offsite storage system and managed by third-party and is made accessible by a web services user. It has become one of the most convenient and efficient ...
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Recent years have shown an increase in the number and complexity of cyberattacks not only on traditional IT infrastructures, but also on smart energy supply networks. Cybercriminals and cyberspies are becoming more so...
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This study presents a comprehensive comparative analysis of the effectiveness of word-level and character-level embeddings in the context of machine learning-based detection of malicious URLs and DGA-generated domains...
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The field of dermatology faces considerable challenges when it comes to early detection of skin cancer. Our study focused on using different datasets, including original data, augmented data, and SMOTE oversampled dat...
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The main requirement in the office sector is the administrative process. At the engineering faculty of the Islamic University of Makassar, some of the administrative processes have used technology to make it easier fo...
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Currently, studies of double nonlinear equations and systems of double nonlinear equations representing many processes found in nature are considered relevant and necessary. These equations and systems, as a rule, are...
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Twister2 is an open-source big data hosting environment designed to process both batch and streaming data at scale. Twister2 runs jobs in both high-performance computing (HPC) and big data clusters. It provides a cros...
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Many Internet protocol (IP) lookup algorithms have been formulated to improve network performance. This study reviewed and experimentally evaluated technologies for trie-based methods that reduce memory access, memory...
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In recent years, there has been significant research focusing on addressing security concerns in single-modal person re-identification (ReID) systems that are based on RGB images. However, the safety of cross-modality...
ISBN:
(纸本)9798331314385
In recent years, there has been significant research focusing on addressing security concerns in single-modal person re-identification (ReID) systems that are based on RGB images. However, the safety of cross-modality scenarios, which are more commonly encountered in practical applications involving images captured by infrared cameras, has not received adequate attention. The main challenge in cross-modality ReID lies in effectively dealing with visual differences between different modalities. For instance, infrared images are typically grayscale, unlike visible images that contain color information. Existing attack methods have primarily focused on the characteristics of the visible image modality, overlooking the features of other modalities and the variations in data distribution among different modalities. This oversight can potentially undermine the effectiveness of these methods in image retrieval across diverse modalities. This study represents the first exploration into the security of cross-modality ReID models and proposes a universal perturbation attack specifically designed for cross-modality ReID. This attack optimizes perturbations by leveraging gradients from diverse modality data, thereby disrupting the discriminator and reinforcing the differences between modalities. We conducted experiments on three widely used cross-modality datasets, namely RegDB, SYSU, and LLCM. The results not only demonstrate the effectiveness of our method but also provide insights for future improvements in the robustness of cross-modality ReID systems.
This article uses the well-known multi-criteria decision-making (MCDM) theory to determine which laptop is the best among those that are currently on the market. To illustrate the importance of decision-making in a cl...
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