Generative image steganography is a technique that directly generates stego images from secret *** traditional methods,it theoretically resists steganalysis because there is no cover ***,the existing generative image ...
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Generative image steganography is a technique that directly generates stego images from secret *** traditional methods,it theoretically resists steganalysis because there is no cover ***,the existing generative image steganography methods generally have good steganography performance,but there is still potential room for enhancing both the quality of stego images and the accuracy of secret information ***,this paper proposes a generative image steganography algorithm based on attribute feature transformation and invertible mapping ***,the reference image is disentangled by a content and an attribute encoder to obtain content features and attribute features,***,a mean mapping rule is introduced to map the binary secret information into a noise vector,conforming to the distribution of attribute *** noise vector is input into the generator to produce the attribute transformed stego image with the content feature of the reference ***,we design an adversarial loss,a reconstruction loss,and an image diversity loss to train the proposed *** results demonstrate that the stego images generated by the proposed method are of high quality,with an average extraction accuracy of 99.4%for the hidden ***,since the stego image has a uniform distribution similar to the attribute-transformed image without secret information,it effectively resists both subjective and objective steganalysis.
Lakes in cold and arid regions play an important role in the daily lives of people. However, the health of the lake ecosystem is seriously affected by climate change, especially human activities. Remote sensing satell...
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The complexity of medical terminologies, variations in professional terms, and the presence of nested entities in the diabetes domain pose challenges for named entity recognition, which has been a focal point of resea...
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In the modern-day economy, a majority of transactions take place in the real estate sector. Financial experts believe it is the finest field to invest in for higher returns. However, there are numerous challenges to c...
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Training a Multilayer Perceptron (MLP) using metaheuristic optimization algorithms serves as a benchmark problem for demonstrating the effectiveness of emerging metaheuristic optimizers. In this study, we explore the ...
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The present scene text extraction methods generally include two independent steps of text detection and text recognition, which is not beneficial to the interaction of feature information and may result in the accumul...
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Infrared imaging systems are often affected by non-uniformity, which can significantly reduce the quality of captured images and hinder subsequent image-processing tasks. Existing infrared image non-uniformity correct...
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The use of blockchain technology is meant to revolutionize the way in which traditional systems work. This technology has paved way for more secure solutions thereby leveraging the concepts of data privacy and authent...
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computer-aided pathology diagnosis based on whole slide images, which is often formulated as a weakly supervised multiple instance learning (MIL) paradigm. Current approaches generally employ attention mechanisms to a...
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Nowadays, the accuracy of remote sensing image target recognition has greatly improved. It enables humans to efficiently monitor crop growth, track climate changes and natural disasters, and even provide critical stra...
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