Ekrem Çetinkaya received his B.Sc. in 2018 and M.Sc. in 2019 from Ozyegin University, Istanbul, Türkiye. He wrote his M.Sc. thesis about image denoising using deep convolutional networks. He is currently pursuing a Ph.D. degree at the University of Klagenfurt, Austria, and working as a researcher on the ATHENA project. His research interests include deep learning, computer vision, and multimedia networking.
The computer vision domain has seen significant advancement in recent years thanks to the prevalence of self-attention. Self-attention modules have proved to be extremely...
Large-scale text-to-image models, looking at you Stable Diffusion, have dominated the machine learning space in recent months. They have shown extraordinary generation performance in...
Diffusion models became the de-facto solution for image generation tasks. They have outperformed generative adversarial networks (GANs) in multiple tasks. It is now possible...
Video has become the preferred way of communication on the Internet nowadays. From getting daily news videos on Twitter to watching never-ending short videos...
Generative AI models have come an extremely long way in the last few years. Their capability increased significantly with the advancement of diffusion models....
Diffusion models became the apple of the machine learning community’s eye in the last months. From generating videos using text prompts to image editing,...
Convolutional neural networks (CNNs) have dominated the computer vision domain for the last decade. From object detection to image classification; they were the state-of-the-art...
Transformers have played a crucial role in natural language processing tasks in the last decade. Their success attributes mainly to their ability to extract...
Artificial Intelligence (AI) field has been busy with handling the burst in generative models for the last couple of months. The open-source release of...
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