Author: Ekrem Çetinkaya

Ekrem Çetinkaya
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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 received his Ph.D. degree in 2023 from the University of Klagenfurt, Austria, with his dissertation titled "Video Coding Enhancements for HTTP Adaptive Streaming Using Machine Learning." His research interests include deep learning, computer vision, video encoding, and multimedia networking.

Semper Ad Meliora: Towards Better Video Codecs with Machine Learning (How Machine Learning ML is used in Video Encoding Part 3)

Increasing demand for video content and stable upgrades in display technology, such as higher resolution, increases the importance of designing efficient video codecs. That...

The Clavis Aurea of Internet Video Delivery: HTTP Adaptive Streaming (How Machine Learning ML is used in Video Encoding Part 2)

We discussed what a video is, why it is essential to reduce its size, and how this compression is done via video encoding. One...

The Sine Qua Non of Video Delivery: Video Encoding (How Machine Learning ML is used in Video Encoding Part 1)

Video has become an essential part of the Internet, and numbers support this statement. Video content was responsible for 82% of the total Internet...

Latest Computer Vision Research Proposes Lumos for Relighting Portrait Images via a Virtual Light Stage and Synthetic-to-Real Adaptation

If you have ever worked with photo editing, then you probably know how cumbersome it can be to adjust the lighting of a portrait...

Meet Phenaki: A Machine Learning-Based Model For Generating Videos From Text Prompts And Uses C-ViViT As Video Encoder

Text-to-image generation is a hot topic in the AI domain, mainly thanks to the open-source release of stable-diffusion. Do you want to see an...

Latest Computer Vision Research Propose An Optimization Framework Called ‘SAMURAI,’ For Joint Camera, Shape, BRDF, And Illumination Estimation

Immersive applications such as augmented reality (AR) and virtual reality (VR) are getting more attention thanks to the rapid advancement in the field. A...

A Latest Machine Intelligence Research Built A Stronger and Faster Baselines Based on a Set of Techniques for Boosting Model Efficiencies

Recognizing human actions in videos is an essential task for many applications. From helping coaches with player analysis in their sports teams to improving...

Researchers Propose a Feature-Space Video Coding Network (FVC) by Performing all Major Operations in the Feature Space

The constant improvement in display technologies and emerging new media representation types such as 360-degree videos enabled videos to have better visual characteristics such...

Latest Computer Vision Research Present a Novel Audio-Visual Framework, ‘ECLIPSE,’ for Long-Range Video Retrieval

Video has become the primary way of sharing information online. Around 80% of the entire Internet traffic consists of video content, and the growth...

Researchers From China Propose ‘NeuralMarker’: A Framework for Learning General Marker Correspondence

Imagine you draw a line in a particular video frame, and you want to preserve that line in the upcoming frames. That means you...

SimpleRecon: A Computer Vision Framework that Produces 3D Reconstructions Without the Use of 3D Convolutions

3D reconstruction is a fundamental problem in computer vision. The goal is to infer the true geometry of an object or a scene given...

WaveOne Research Proposes A New Machine Learning-Based Algorithm For Video Coding, Learned End-To-End For The Low-Latency Mode

Video content continues to dominate Internet traffic by taking more than 80% of the traffic share in 2022. Although performance improvement is significant in...

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