The mobile radar platform will lead to defocusing of the range-Doppler spectra of the echo signal, which will reduce the effect of multi-pulse coherent accumulation and target detection performance. In the one-transmi...
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Water quality prediction methods forecast the future short or long-term trends of its changes, providing proactive advice for water pollution prevention and control. Existing water quality prediction methods only cons...
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Low-density parity-check (LDPC) codes are integral to modern communication systems, including the 5G standard, which supports a new service type known as massive machine type communications (mMTC). mMTC terminals, typ...
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The structure of most current multi-band stealth materials is very complex, making large-scale production and application difficult. We have demonstrated a structure that not only achieves multi-band stealth functiona...
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The supply chain comprises numerous components/ identities as suppliers, manufacturers, factories, warehouses, distributing agents, etc. These personalities are engaged in delivering raw materials, and components, whi...
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Foreground segmentation is an important part of computer vision and has many useful applications, such as tracking objects and detecting anomalies. However, deep learning models often struggle with the difficult task ...
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Foreground segmentation is an important part of computer vision and has many useful applications, such as tracking objects and detecting anomalies. However, deep learning models often struggle with the difficult task of preserving small details when extracting features, which is crucial for accurately segmenting edges. To overcome this challenge, we have developed a new segmentation network with a cascading architecture. This innovative approach gradually incorporates finer details into higher-level features, continuously improving the segmentation results. We have thoroughly evaluated our method using the challenging CDnet2014 dataset, and it has shown exceptional performance with an impressive F-measure of 0.9868. This research demonstrates the potential of cascading networks to greatly improve foreground segmentation in computer vision applications, and it is completely original work.
In the rapidly advancing field of bioinformatics, sequence alignment is a pivotal task for elucidating genetic statistics and evolutionary relationships. As the volume and complexity of biological data continue to gro...
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Face is an important source of information for interpersonal communication and recognition, so facial reconstruction technology has always been a research focus in the field of computer *** present a deep learning-bas...
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multi-layer images are currently the most prominent scene representation for viewing natural scenes under full-motion parallax in virtual reality. Layers ordered in diopter space contain color and transparency so that...
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multi-layer images are currently the most prominent scene representation for viewing natural scenes under full-motion parallax in virtual reality. Layers ordered in diopter space contain color and transparency so that a complete image is formed when the layers are composited in a view-dependent manner. Once baked, the same limitations apply to multi-layer images as to conventional single-layer photography, making it challenging to remove obstructive objects or otherwise edit the content. Object removal before baking can benefit from filling disoccluded layers with pixels from background layers. However, if no such background pixels have been observed, an inpainting algorithm must fill the empty spots with fitting synthetic content. We present and study a multi-layer inpainting approach that addresses this problem in two stages: First, a volumetric area of interest specified by the user is classified with respect to whether the background pixels have been observed or not. Second, the unobserved pixels are filled with multi-layer inpainting. We report on experiments using multiple variants of multi-layer inpainting and compare our solution to conventional inpainting methods that consider each layer individually.
Accurate time plays an important role in deep space exploration, navigation and positioning. With the development of technology, both the performance requirements of the punctual system and the accuracy of the meterin...
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