Maintaining my open-source packages takes a huge amount of time.
More sponsors = More motivation 🚀

🧐 about me

• Passionate about Machine Learning/Deep Learning, Computer Vision
• Ph.D. cand. in Informatics (multi-modal video understanding), BSc and Msc. in Engineering (deep learning/computer vision)
• Loving research (📈 200+ citations) and open source (📈 2 million+ downloads)

🔥 some of my opensource works:

A lightweight vision library for performing large scale object detection/ instance segmentation:

• https://github.com/obss/sahi

Packaged version of ultralytics/yolov5 + many extra utilities:

• https://github.com/fcakyon/yolov5-pip

Deep learning based content moderation from text, audio, video & image input modalities:

• https://github.com/fcakyon/content-moderation-deep-learning

Easiest way of fine-tuning HuggingFace video classification models:

• https://github.com/fcakyon/video-transformers

Easy-to-use, class-balanced, cross-entropy and focal loss implementation for Pytorch:

• https://github.com/fcakyon/balanced-loss

A simple Streamlit Component to compare images with a slider in Streamlit apps:

• https://github.com/fcakyon/streamlit-image-comparison

Packaged, Pytorch-based, easy to use, cross-platform version of the CRAFT text detector:

• https://github.com/fcakyon/craft-text-detector

Make your own dataset for object detection and transform the format to coco json format:

• https://github.com/fcakyon/labelme2coco

📜 some of my published/submitted papers:

• Deep Architectures for Content Moderation and Movie Content Rating
  (Preprint)

• Sequence Models for Drone vs Bird Classification
  (Preprint)

• Slicing Aided Hyper Inference and Fine-tuning for Small Object Detection
  (Accepted at ICIP 2022)

• Drone-vs-Bird Detection Challenge at IEEE AVSS2021
  (Published at AVSS 2021)

• Track Boosting and Synthetic Data Aided Drone Detection
  (Published at AVSS 2021)

• Automated question generation and question answering from Turkish texts
  (Accepted at SCI Journal, 2022)

• Instagram Fake and Automated Account Detection
  (Published at INISTA 2019)