Advanced gan models for super resolution problem
➤ Gửi thông báo lỗi ⚠️ Báo cáo tài liệu vi phạmNội dung chi tiết: Advanced gan models for super resolution problem
Advanced gan models for super resolution problem
VIETNAM NATIONAL UNIVERSITY HO CHI MINH UNIVERSITY OF TECHNOLOGY Faculty of Computer Science and EngineeringGRADUATION THESISADVANCED GAN MODELS FOR S Advanced gan models for super resolution problem SUPER-RESOLUTION PROBLEMMajor : Computer ScienceCouncil : Computer Science 3 (English Program)Instructor: Dr. Nguyen Due DungReviewer: Dr. TYan Tuan Anil0O0St udents : Truong Minh Duy - 1652113Nguyen Hoang Thuan - 1752054Ho Chi Minh City, July 2021AcknowledgementWe would love to show our deep and ho Advanced gan models for super resolution problem nest gratitude to our instructor Dr. Nguyen Due Dung. His compassion and instructions are invaluable in this research.We also sincerely thank all of tAdvanced gan models for super resolution problem
he faculty’s lecturers. Without their guidance, wo cannot have ourselves equipped with enough knowledge to carry out this research. Not only that, theVIETNAM NATIONAL UNIVERSITY HO CHI MINH UNIVERSITY OF TECHNOLOGY Faculty of Computer Science and EngineeringGRADUATION THESISADVANCED GAN MODELS FOR S Advanced gan models for super resolution problem rateful to our family and friends for being the moral support during all this lime.Finally, we wish them happiness, passion, and success in any path that they choose.Studentshttps://khothuvien.cori!Abstract111 recent years, it is undoubted that machine learning and its subset, deep learning. is a fr Advanced gan models for super resolution problem ontier in Artificial Intelligence research. Generative Adversarial Networks (GANs). an emergent subclass of deep learning, has attracted considerableAdvanced gan models for super resolution problem
public al tention in the research area of unsupervised learning for its powerful data generation ability. This model can generate incredibly realisticVIETNAM NATIONAL UNIVERSITY HO CHI MINH UNIVERSITY OF TECHNOLOGY Faculty of Computer Science and EngineeringGRADUATION THESISADVANCED GAN MODELS FOR S Advanced gan models for super resolution problem in real world problems is still challenging due to many reasons such as unstable training, the lack of reasonable evaluation metrics, the poor diversity of output image. Our research focuses on improving GAN models per formance in a notoriously challenging ill posed problem - single image super-res Advanced gan models for super resolution problem olution (S1SR). Specifically, wo inspect and analyze ESRGAN' model, which is a seminal work-in perceptual SISR field. During our research, we proposeAdvanced gan models for super resolution problem
changes in both model architecture and learning strategy to further enhance the output in two directions: image quality and image diversity. At the enVIETNAM NATIONAL UNIVERSITY HO CHI MINH UNIVERSITY OF TECHNOLOGY Faculty of Computer Science and EngineeringGRADUATION THESISADVANCED GAN MODELS FOR S Advanced gan models for super resolution problem lity Evaluator.CNNConvolutional Neural Network.DCTDiscrete Cosine Transform.DFTDiscrete Fourier Transform.FFTFast Fourier Transform.FIDFrechet Inception Distance.GA NsGenerative Adversarial Networks.HRHigh-Resolution.IQAImage Quality Assessment.LPIPSLearned Perceptual Image Patch Similarity.LRLow-Re Advanced gan models for super resolution problem solution.MOSMean Opinion Score.MSEMean Square Error.VIETNAM NATIONAL UNIVERSITY HO CHI MINH UNIVERSITY OF TECHNOLOGY Faculty of Computer Science and EngineeringGRADUATION THESISADVANCED GAN MODELS FOR SVIETNAM NATIONAL UNIVERSITY HO CHI MINH UNIVERSITY OF TECHNOLOGY Faculty of Computer Science and EngineeringGRADUATION THESISADVANCED GAN MODELS FOR SGọi ngay
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