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Mesh Image Reconstruction using Encoders: A Review

Prof. Sonali Guhe, Rovin Singh, Pranav  P Ninawe

 Asst. Prof Dept of Information Technology

G.H.Raisoni College of Engineering, Nagpur.

Abstract – Image Reconstruction is the one of the most machine learning but what if you have to reconstruct a low pixel image into a clear image and detect the predictable entity and thus provide informational insights regarding the image also for example if there is a mesh image that is a broken or distorted image having a void or at any pixel location of they image .Then such image is regenerated or can be termed as reconstructed using our own model. Learning-based methods, especially encoder-based models, have achieved good results in image reconstruction. This review article examines encoder-based models, including autoencoders, convolutional neural networks (CNN), and artificial adversarial networks (GAN), and their performance in various image reconstruction tasks. . Challenges and future directions of encoder-based image reconstruction are also discussed.