Titlebook: Computer Vision and Image Processing; 4th International Co Neeta Nain,Santosh Kumar Vipparthi,Balasubramanian Conference proceedings 2020 S

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Anomalous Event Detection and Localization Using Stacked Autoencoderlow using stacked autoencoder. Autoencoder extracts high-level structural information from motion magnitudes to distinguish between normal and anomalous behaviors. The performance of proposed approach is experimentally evaluated on standard UCSD and UMN dataset developed for anomaly detection. Resul

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DNN Based Adaptive Video Streaming Using Combination of Supervised Learning and Reinforcement Learnid maintain smooth playback. Training can happen on Personal Computer (PC) based server or edge server setup as well as On-Device, which can even be beneficial in providing user personalization based on network throughput collected on the device. It has been shown that this method will give users a s

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A Deep Convolutional Neural Network Based Approach to Extract and Apply Photographic Transformationsk (CNN) is introduced that can transfer the photographic filter and effects from a given reference image to a desired target image via adaptively predicting the parameters of the transformations that were applied on the reference image. These predicted parameters are then applied to the target image

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https://doi.org/10.1007/978-1-4302-2642-0characterize their profession. In this paper, the profession of a writer is identified by analyzing the features of writer’s offline handwritten images. The previous work mostly includes determining various traits like honesty, emotional stability of a writer. The Proposed work uses the CNN based mo

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Maurizio Delmonte,Davide Moro,Andy McKaylow using stacked autoencoder. Autoencoder extracts high-level structural information from motion magnitudes to distinguish between normal and anomalous behaviors. The performance of proposed approach is experimentally evaluated on standard UCSD and UMN dataset developed for anomaly detection. Resul

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Maurizio Delmonte,Davide Moro,Andy McKayd maintain smooth playback. Training can happen on Personal Computer (PC) based server or edge server setup as well as On-Device, which can even be beneficial in providing user personalization based on network throughput collected on the device. It has been shown that this method will give users a s