Data watermark is of the surmount importance for data trading. Most of the data in the current data trading market is stored in the form of spreadsheets, yet there are few watermarking schemes specifically designed fo...
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Camouflaged object detection is focused on segmenting objects concealed within their surroundings. This technology can be applied in various fields such as medical image analysis, wildlife conservation, autonomous dri...
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ISBN:
(纸本)9789819788576;9789819788583
Camouflaged object detection is focused on segmenting objects concealed within their surroundings. This technology can be applied in various fields such as medical image analysis, wildlife conservation, autonomous driving, and others. Existing semi-supervised camouflage object detection methods often suffer from poor network performance due to the accumulation of incorrect pseudo labels, and they fail to fully utilize multi-scale features or account for the diverse scale contexts necessary for various sizes of camouflage objects. In this paper, we propose an innovative semi-supervised learning strategy. We employ a dual-branch network named CAMNet, utilizing salient maps corresponding to camouflage objects to aid detection. We also introduce a Multi-Information Fusion Feature Perception module (MIF) and an Adaptive Receptive Field Selection module (ARFS), which are integrated into the network. Ultimately, we perform thorough comparative experiments on the R2C7K, COD-Water, and COD-Jungle datasets, showcasing superior performance in contrast to current state-of-the-art methods. We also conduct ablation experiments, further confirming the effectiveness of the proposed modules.
Analyzing sequential data is crucial in many domains, particularly due to the abundance of data collected from the Internet of Things paradigm. Time series classification, the task of categorizing sequential data, has...
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Brain-computer interface (BCI) connects the brain and computer. Support for people with disabilities is a frequent topic in studies on steady-state visual evoked potential (SSVEP)-BCI. This study aimed to adapt SSVEP-...
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ISBN:
(纸本)9783031628481;9783031628498
Brain-computer interface (BCI) connects the brain and computer. Support for people with disabilities is a frequent topic in studies on steady-state visual evoked potential (SSVEP)-BCI. This study aimed to adapt SSVEP-BCI for individuals with aphasia accompanied by paralysis. The subject of this study suffered from aphasia due to stroke and experienced decreased vision in the right eye due to right hemiplegia. We conducted a comparison of SSVEP-BCI accuracy using an electroencephalogram (EEG) obtained from the primary visual cortex (whole area), the left primary visual cortex (left area), and the right primary visual cortex (right area). We investigated the measurement site of SSVEP-BCI for BCI accuracy by measuring areas such as whole area, left area, and right area, for which the accuracy rates were 81.03%, 43.96%, and 86.97%, respectively. Therefore, based on these results, EEG from the right area should be used for the subjects in this study. These results underscore the importance of selecting measurement sites that consider the brain function of aphasia patients.
With the emergence and rapid development of Transformers, medical image segmentation has also been revolutionized by Transformers due to their ability to encode long-range dependencies. Despite their advantages, Trans...
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Semi-supervised learning, a system dedicated to making networks less dependent on labeled data, has become a popular paradigm due to its strong performance. A common approach is to use pseudo-labels with unlabeled dat...
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In recent years, there has been a growing need for techniques that enable users to explain the basis for decisions made by neural networks in image recognition problems. While many conventional methods have focused on...
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For graphs G and H, the multicolor Ramsey number rk,1(G, H) is the minimum N such that any edge-coloring of KN by k+ 1 colors contains a monochromatic G in the first k colors or a monochromatic H in the last color. In...
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Today, computer technologies are becoming more accessible to everyone. Even at a young age, people are confronted with information technologies (IT) in their daily lives. Therefore, computerscience is becoming increa...
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Few-shot learning is crucial in machine learning and computer vision. It enables models to recognize new objects with limited labeled data, addressing the challenge of data scarcity and expanding the application of ma...
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