Öğr. Gör. Dr. OĞUZHAN ÖNAL

Makaleler 3

1. Unsafe-Net: YOLO v4 and ConvLSTM based computer vision system for real-time detection of unsafe behaviours in workplace

ÖNAL O., DANDIL E.

Multimedia Tools and Applications , cilt.84, sa.29, ss.34967-34993, 2025 (SCI-Expanded, Scopus)

2. Video dataset for the detection of safe and unsafe behaviours in workplaces

Önal O., Dandıl E.

DATA IN BRIEF , cilt.56, ss.110791-110802, 2024 (ESCI, Scopus)

3. Object Detection for Safe Working Environments using YOLOv4 Deep Learning Model

ÖNAL O., DANDIL E.

Avrupa Bilim ve Teknoloji Dergisi , sa.26, ss.343-351, 2021 (TRDizin)

Hakemli Bilimsel Toplantılarda Yayımlanmış Bildiriler 1

1. Real-Time Vehicle Tracking System Based on YOLO and Stereo Vision

DANDIL E., Sivrikaya A. S., ÖNAL O., Kaçar S.

5th International Conference on Intelligence-Based Transformations of Technology and Business Trends, ICITTBT 2025, Tirana, Arnavutluk, 29 - 30 Mayıs 2025, cilt.2669 CCIS, ss.708-726, (Tam Metin Bildiri)

Kitaplar 1

1. Real-Time Vehicle Tracking System Based on YOLO and Stereo Vision

DANDIL E., SİVRİKAYA A. S., ÖNAL O., KAÇAR S.

AI and Digital Transformation: Opportunities, Challenges, and Emerging Threats in Technology, Business, and Security (Communications in Computer and Information Science), Springer, Cham., ss.708-726, 2025

Yayınlar & Eserler

1. Unsafe-Net: YOLO v4 and ConvLSTM based computer vision system for real-time detection of unsafe behaviours in workplace

2. Video dataset for the detection of safe and unsafe behaviours in workplaces

3. Object Detection for Safe Working Environments using YOLOv4 Deep Learning Model

1. Real-Time Vehicle Tracking System Based on YOLO and Stereo Vision

1. Real-Time Vehicle Tracking System Based on YOLO and Stereo Vision