914 research outputs found

    Light Field Denoising via Anisotropic Parallax Analysis in a CNN Framework

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    Light field (LF) cameras provide perspective information of scenes by taking directional measurements of the focusing light rays. The raw outputs are usually dark with additive camera noise, which impedes subsequent processing and applications. We propose a novel LF denoising framework based on anisotropic parallax analysis (APA). Two convolutional neural networks are jointly designed for the task: first, the structural parallax synthesis network predicts the parallax details for the entire LF based on a set of anisotropic parallax features. These novel features can efficiently capture the high frequency perspective components of a LF from noisy observations. Second, the view-dependent detail compensation network restores non-Lambertian variation to each LF view by involving view-specific spatial energies. Extensive experiments show that the proposed APA LF denoiser provides a much better denoising performance than state-of-the-art methods in terms of visual quality and in preservation of parallax details

    An Improved Ant Colony Algorithm for New energy Industry Resource Allocation in Cloud Environment

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    The new energy industry development is affected by many factors. Among them, the resources utilization ratio is a major reason for the low productivity of enterprises. As the core problem of cloud computing, the resource allocation problem has been widely concerned by the people, and the resource allocation problem of the new energy industry as the key to energy innovation and transformation should be more paid attention to. In multi-resource cloud computing scenarios, requests made by users often involve multiple types of resources. Traditional resource allocation algorithms have a single optimization object, typically time efficiency. In order to achieve cluster load balancing, utilization of system resources and improvement of system work efficiency, this paper proposes a new cloud computing allocation algorithm based on improved ant colony algorithm. According to the limit conditions of cloud computing environment and computing resources, this paper finds the shortest response time of all resource nodes and gets a set of best available nodes. This method can meet the quality requirements of cloud computing, and the task completion time of the improved algorithm is shorter, the number of algorithm iterations is less, and the load balancing effect is better. Through MATLAB simulation experiments, the effectiveness of the proposed method is verified

    STK11 loss and SMARCB1 deficiency mutation in a dedifferentiated lung cancer patient present response to neo-adjuvant treatment with pembrolizumab and platinum doublet: A case report

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    Cancers harboring serine threonine kinase (STK11) alteration or SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily B, member 1 (SMARCB1) mutation are conventionally considered as treatment-refractory to immune checkpoint inhibitors or chemotherapy, respectively. However in the present report, we demonstrated a case of dedifferentiated non-small cell lung cancer, characterized by STK11 loss (due to promoter loss) mutation co-mutated with SMARCB1 deficiency mutation, has achieved significantly partial response to neo-adjuvant treatment with pembrolizumab and platinum doublet regimen. Our case highlighted that either STK11 loss, or SMARCB1 deficiency mutation, might not be used to select patients for PD-(L)1 blockade therapy or chemotherapy, respectively. SKT11 loss accompanied with SMARCB1 deficiency mutation may benefit from immunotherapy combined with chemotherapy
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