Top 10 Object Detection Models in 2023!
A Comprehensive Guide to Revolutionizing Object Detection with Deep Learning.
“Object detection is one of the most exciting and challenging problems in computer vision, and deep learning has emerged as a powerful tool to tackle it.” — Dr. Liang-Chieh Chen
Object detection is a fundamental task in computer vision that involves identifying and localizing objects within an image. Deep learning has revolutionized object detection, allowing for more accurate and efficient detection of objects in images and videos. In 2023, there are several deep-learning models that are making significant advancements in object detection. Here are the top 10 deep-learning models for object detection in 2023:
1. YOLOv7
YOLOv7 or You Only Look Once version-7, is a state-of-the-art deep learning model for object detection. YOLOv7 is based on the original YOLO architecture but uses a more efficient backbone network and a new set of detection heads. YOLOv7 can detect objects in real-time with high accuracy and can be trained on large datasets. The model is also very efficient and can run on low-end devices.
Pros:
- Very fast and efficient object detection
- High accuracy on large datasets
