Author :
Hasib Al Muzdadid
Department of Computer Science & Engineering,
Rajshahi University of Engineering & Technology (RUET)
Portfolio: https://hasibalmuzdadid.github.io
LinkedIn: https://www.linkedin.com/in/hasibalmuzdadid
You Only Look Once or YOLO is an algorithm that detects and recognizes various objects in real time. Object detection in YOLO is done as a regression problem and provides the class probabilities of the detected images. It employs convolutional neural networks (CNN) to detect objects in real-time. As the name suggests, the algorithm requires only a single forward propagation through a neural network to detect objects. This means that prediction in the entire image is done in a single algorithm run. The CNN is used to predict various class probabilities and bounding boxes simultaneously.
YOLO algorithm improves the speed of detection because it can predict objects in real-time. This is a predictive technique that provides accurate results with minimal background errors. The algorithm has excellent learning capabilities that enable it to learn the representations of objects and apply them in object detection.
YOLO algorithm improves the speed of detection because it can predict objects in real-time. This is a predictive technique that provides accurate results with minimal background errors. The algorithm has excellent learning capabilities that enable it to learn the representations of objects and apply them in object detection.
The ideas were described in these two YOLO papers: Redmon et al., 2016 and Redmon and Farhadi, 2016.
This was implemented for the completion of the Convolutional Neural Networks course offered by DeepLearning.AI on Coursera which is also a part of Deep Learning Specialization offered by DeepLearning.AI on Coursera.
Language used : Python
Development Tools : Jupyter Notebook
Platform : Google Colab
Accomplishments :
| Course | Achievement |
|---|---|
| Convolutional Neural Networks | Certificate |
| Deep Learning Specialization | Certificate |