This study is related to a system that enables elderly people to communicate interactively with young people who use existing message exchange services by simply speaking to an avatar on a tablet PC, without having to...
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Amorphous indium gallium zinc oxide (a-IGZO)-based thin film transistors (TFTs) are increasingly becoming popular because of their potential in futuristic applications, including CMOS technology. Given the demand for ...
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Semi-supervised learning has been an important approach to address challenges in extracting entities and relations from limited data. However, current semi-supervised works handle the two tasks (i.e., Named Entity Rec...
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Metasurfaces offer remarkable control over different characteristics of the electromagnetic waves. They can be used to modify the phase, amplitude, polarization, and direction of reflection associated with an incoming...
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ISBN:
(数字)9789463968119
ISBN:
(纸本)9798350359497
Metasurfaces offer remarkable control over different characteristics of the electromagnetic waves. They can be used to modify the phase, amplitude, polarization, and direction of reflection associated with an incoming incident field. This behavior can be mathematically represented using the generalized sheet transition conditions (GSTCs) (K. Achouri and C. Caloz, Electromagnetic Metasurfaces: Theory and Applications, Wiley, 2021). GSTCs connect the electromagnetic fields on the two sides of the sheet using equivalent bianisotropic electric and magnetic susceptibility tensors. These tensors account for the cumulative electric and magnetic polarization density effect of the unit-cell configurations on the electromagnetic fields.
Metasurfaces are expected to revolutionize wireless communications due to their ability to enhance different characteristics of electromagnetic wave propagation channels. The response of a metasurface to an electromag...
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ISBN:
(数字)9789463968119
ISBN:
(纸本)9798350359497
Metasurfaces are expected to revolutionize wireless communications due to their ability to enhance different characteristics of electromagnetic wave propagation channels. The response of a metasurface to an electromagnetic excitation is determined by the geometry, the material composition, and the spatial arrangement of its sub-wavelength unit cells. This response can be considered as a spatiotemporal discontinuity in the field and can be mathematically described using the so-called generalized sheet transition conditions (GSTCs) (K. Achouri and C. Caloz, Electromagnetic Metasurfaces: Theory and Applications, Wiley, 2021). The GSTCs connect the electromagnetic fields on two sides of the metasurface using the electric and magnetic bianisotropic susceptibility tensors which effectively represent the metasurface.
Although supervised image denoising networks have shown remarkable performance on synthesized noisy images, they often fail in practice due to the difference between real and synthesized noise. Since clean-noisy image...
Although supervised image denoising networks have shown remarkable performance on synthesized noisy images, they often fail in practice due to the difference between real and synthesized noise. Since clean-noisy image pairs from the real world are extremely costly to gather, self-supervised learning, which utilizes noisy input itself as a target, has been studied. To prevent a self-supervised denoising model from learning identical mapping, each output pixel should not be influenced by its corresponding input pixel; This requirement is known as J-invariance. Blind-spot networks (BSNs) have been a prevalent choice to ensure J-invariance in self-supervised image denoising. However, constructing variations of BSNs by injecting additional operations such as downsampling can expose blinded information, thereby violating J-invariance. Consequently, convolutions designed specifically for BSNs have been allowed only, limiting architectural flexibility. To overcome this limitation, we propose PUCA, a novel J-invariant U-Net architecture, for self-supervised denoising. PUCA leverages patch-unshuffle/shuffle to dramatically expand receptive fields while maintaining J-invariance and dilated attention blocks (DABs) for global context incorporation. Experimental results demonstrate that PUCA achieves state-of-the-art performance, outperforming existing methods in self-supervised image denoising.
Centralized machine learning algorithms in vehicular networks face privacy and resource constraints. Federated Learning (FL) addresses these by enabling collaborative model training without sharing raw data. To incent...
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A meta-optic platform for accelerating object classification is demonstrated. End-to-end design is used to co-optimize the optical and digital systems resulting in a high-speed and robust classifier with 93.1% accurac...
We propose Text2Scene, a method to automatically create realistic textures for virtual scenes composed of multiple objects. Guided by a reference image and text descriptions, our pipeline adds detailed texture on labe...
We propose Text2Scene, a method to automatically create realistic textures for virtual scenes composed of multiple objects. Guided by a reference image and text descriptions, our pipeline adds detailed texture on labeled 3D geometries in the room such that the generated colors respect the hierarchical structure or semantic parts that are often composed of similar materials. Instead of applying flat stylization on the entire scene at a single step, we obtain weak semantic cues from geometric segmentation, which are further clarified by assigning initial colors to segmented parts. Then we add texture details for individual objects such that their projections on image space exhibit feature embedding aligned with the embedding of the input. The decomposition makes the entire pipeline tractable to a moderate amount of computation resources and memory. As our framework utilizes the existing resources of image and text embedding, it does not require dedicated datasets with high-quality textures designed by skillful artists. To the best of our knowledge, it is the first practical and scalable approach that can create detailed and realistic textures of the desired style that maintain structural context for scenes with multiple objects.
Lilies are popular in the global flower market, but consumers often lack information about specific varieties. To address this issue, this paper proposes a computer recognition platform based on the Vision Transformer...
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