Author: 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 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.

Meet MOAT: An Artificial Intelligence (AI) Model that Combines Convolution and Attention Operations to Achieve Powerful Vision Models

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...

Meet ReCo: An AI Extension for Diffusion Models to Enable Region Control

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...

This Artificial Intelligence (AI) Paper From UC Berkeley Presents A General Navigation Model (GNM) From An Aggregated Multirobot Dataset To Drive Any Robot

Although their presence is not as significant as projected by Sci-Fi movies from the 90s, robots are becoming essential in our daily lives with...

Meet SinFusion: An Artificial Intelligence (AI) Model That Generates Realistic Images And Videos Using A Single Input

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...

This Artificial Intelligence (AI) Method Uses Fragment Sampling to Efficiently Determine Video Quality

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...

ByteDance AI Researchers Introduce ‘MagicVideo,’ an Efficient Text-to-Video Generation Framework based on Latent Diffusion Models

Generative AI models have come an extremely long way in the last few years. Their capability increased significantly with the advancement of diffusion models....

Meet MinD-Vis: An AI Model That Can Reconstruct What You See Using Brain Scans

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,...

This Artificial Intelligence (AI) Model Knows How to Detect Novel Objects During Object Detection

Object detection has been an important task in the computer vision domain in recent decades. The goal is to detect instances of objects, such...

This AI Model Integrates Feature Pyramids into Vision Transformers to Enhance Their Capability

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...

Google Research Proposes an Artificial Intelligence (AI) Model to Utilize Vision Transformers on Videos

Transformers have played a crucial role in natural language processing tasks in the last decade. Their success attributes mainly to their ability to extract...

Meet TECO: An Efficient Video Prediction AI Model That Can Generate Long, Temporally Consistent Video For Complex Datasets In 3D scenes

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...

This Artificial Intelligence Paper Proposes ‘SuperGlue,’ A Graph Neural Network That Simultaneously Performs Context Aggregation, Matching, And Filtering of Local Features for Wide-Baseline Pose...

Imagine you have two pictures of the same scene taken from different angles. Most of the objects in both pictures are the same, just...

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