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Yağmur Çiğdem Aktaş

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Complete MLOPS Cycle for a Computer Vision Project

These days, we encounter (and maybe produce on our own) many computer vision projects, where AI is the hottest topic for new technologies…

Nov 28, 2024

Complete MLOPS Cycle for a Computer Vision Project

Nov 28, 2024

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TDS Archive

Object Detection with Convolutional Neural Networks

Multi-Stage(RCNN, Fast RCNN, Faster RCNN) and Single Stage (SSD, YOLO) architectures for object detection and their usage to train your own…

Jan 30, 2022

Object Detection with Convolutional Neural Networks

Jan 30, 2022

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Object Detection using Lidar

State-of-the-art AI Models for processing Lidar data in order to detect objects: Pointnet, Voxelnet, SECOND, and Pointpillar are explained

Jul 28, 2022

Object Detection using Lidar

Jul 28, 2022

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AI Advances

Stable Diffusion 101: From the Eye of a Computer Vision Researcher

Start Discovering Stable Diffusion by studying the model architecture, experiencing inference with various adapters and methods like…

May 2

Stable Diffusion 101: From the Eye of a Computer Vision Researcher

May 2

Neural Networks Fundamentals

A quick intro for Neural Networks, Unsupervised and Supervised Learning, the difference between Regression and Classification and their…

Apr 28

Neural Networks Fundamentals

Apr 28

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Data Science Collective

CLIP: The Multimodal Powerhouse Transforming Computer Vision

When I first met with CLIP and its performance, it impressed me so much that whenever I start a new project, I take CLIP’s performance as a…

Mar 24

CLIP: The Multimodal Powerhouse Transforming Computer Vision

Mar 24

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AI Advances

CLIP vs DINOv2: Which one is better for image retrieval?

Compare CLIP and DINOv2 for image retrieval tasks, and learn about their specific powers and weaknesses to decide the best one for your…

Feb 13

CLIP vs DINOv2: Which one is better for image retrieval?

Feb 13

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TDS Archive

Track Computer Vision Experiments with MLflow

Discover how to set up an efficient MLflow environment to track your experiments, compare and choose the best model for deployment

Dec 26, 2024

Track Computer Vision Experiments with MLflow

Dec 26, 2024

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TDS Archive

An easy way to understand GIT

Intermediate git commands and their meanings explained

Nov 4, 2022

An easy way to understand GIT

Nov 4, 2022

3D Multi-Object Tracking using Lidar

Introduction to Lidar, Autonomous Driving Public Dataset Types, State of the Art Object Recognition Models for Lidar, and a Kalman…

Jul 28, 2022

3D Multi-Object Tracking using Lidar

Jul 28, 2022

Yağmur Çiğdem Aktaş

Yağmur Çiğdem Aktaş

Computer Vision Enthusiastic & Researcher www.linkedin.com/in/yağmur-cigdem-aktas https://github.com/YCAyca

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