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This repository holds the downstream task of Face Mask Classification performed on Self Currated Custom Dataset with various State of the Art deep learning models like ViT, BeIT, DeIT, LeViT, ConvNeXt, VGG16, EfficientNetV2, RegNet and MobileNetV3.
The analysis of several vision-based transformers is the main emphasis of this project, which also analyzes their distinctive properties and evaluates how well they work using a common dataset. The study intends to obtain insights into the strengths and shortcomings of various transformer designs created for computer vision tasks.
Final assignment in the NLP course at the Technion (IEM097215). In this assignment we propose a novel architecture to handle both Text-to-Image translation and Image-to-Text translation tasks on paired data, using a unified architecture of transformers and CNNs and enforcing cycle consistency.