Image Data and Computer Vision: I have extensive experience working with image data in the field of computer vision. I have successfully completed my thesis and published a paper on image quality assessment, demonstrating my understanding and expertise in evaluating image fidelity and perceptual quality.GAN-based Projects: I have worked on various projects leveraging Generative Adversarial Networks (GANs) for tasks such as image augmentation, image editing, and image reconstruction. By harnessing the power of GANs, I have explored techniques to generate realistic and diverse images, enhance existing images, and reconstruct missing or corrupted image data.Super Resolution: I have actively worked in the field of super resolution, which involves enhancing the resolution and quality of low-resolution images. By utilizing advanced algorithms and techniques, I have developed solutions to generate high-resolution images with improved details and clarity.Transformer Models: I have utilized transformer models, specifically ViT (Vision Transformer) and Swin Transformer, in the context of High Dynamic Range (HDR) imaging. These models have allowed me to effectively process and enhance HDR images, enabling better representation and preservation of details in scenes with varying lighting conditions.Diverse Project Experience: Throughout my coursework, I have completed a range of projects covering various computer vision tasks. These include Optical Character Recognition (OCR), handwritten detection and classification, 3D object detection, and modifying light contrast using deep reinforcement learning techniques, specifically employing Q-learning algorithms.By combining theoretical knowledge, practical experience, and a deep understanding of computer vision techniques, I have successfully tackled challenging projects in the field. I am passionate about pushing the boundaries of computer vision and utilizing cutting-edge methods to solve real-world problems.