This paper investigates differences in normal force for different tracing directions on the basis of friction, taking into account individual differences. The normal force and friction coefficient were measured when s...
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In SAR image detection, small target ships are susceptible to interference from clutter and noise, making accurate classification and detection challenging. Despite significant progress in this field, there has been a...
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Human neuroimaging datasets provide rich multi-scale spatiotemporal information about the state of the brain. Most current methods, such as spectral analysis, focus on a single facet of these datasets and do not take ...
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Similarity-based classification framework is extensively used to address the problem of multi-label learning. Through this research, we establish the connection between similarity-based classification with many popula...
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Existing cross-modal hashing methods have made progress in enhancing retrieval capabilities and reducing model size, but they struggle to balance retrieval performance across different channels, leading to increased *...
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The images taken under varying lighting or adverse weather conditions exhibit different distributions in high-dimensional space, and make object detection networks perform poorly. In this paper, we propose a domain ad...
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Accurate flight trajectory prediction is crucial for enhancing the overall efficiency of air traffic management. However, existing methods often overlook the importance of capturing flight trends and pay insufficient ...
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The capabilities of current robotic applications are significantly constrained by their limited ability to perceive and understand their surroundings. The Semantic Web aims to offer general, machine-readable knowledge...
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In this study, we introduce a novel method for enhancing diffusion images through a hybrid partial differential equation approach. This approach incorporates pulse filtering, an enhanced forward-backward diffusion fil...
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ISBN:
(纸本)9789819609130;9789819609147
In this study, we introduce a novel method for enhancing diffusion images through a hybrid partial differential equation approach. This approach incorporates pulse filtering, an enhanced forward-backward diffusion filter, and the total variational diffusion method. Our algorithm effectively enhances small boundaries in images by utilizing an improved hybrid partial differential equation diffusion image filtering algorithm. By utilizing a pulse filter with specific parameter constraints, we enhance the processing capabilities for strong boundaries. Additionally, we employ the level set method to eliminate sawtooth artifacts at boundaries and enhance boundary smoothness. Furthermore, we propose a biorthogonal filtering method based on a degraded model that achieves biorthogonal mapping in the spatial domain, ensuring the invertibility of the degraded extended image concerning the degraded model. Simulation results demonstrate the superiority of our method compared to other techniques. The resulting amplified images exhibit excellent photorealism, with improved boundary details for both weak and medium brightness levels. This method effectively preserves image boundary details while effectively reducing noise.
Text-line segmentation is still considered challenging for complex background scene images. The success of text detection and recognition depends on the success of the text segmentation. This study presents a new meth...
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