RetinaNet
RetinaNet is one of the best object detection models and an alternative to YOLO, which uses a pyramid network and focal loss function. It has developed new techniques to address the critical challenges encountered in object detection.
Features
- They are designed to handle various object detection tasks of multiple sizes.
- It contains a multi-scale feature to let the model detect different objects of different scales.
- Detects small to large objects in the same image, resulting in model accuracy.
- The focal loss function assigns weight to hard-to-classify objects for easy classification.
Pros
- Able to handle imbalance of class, resulting in accuracy.
- Designed to run efficiently and easy to deploy on low-end devices.
Cons
- It encounters a lot of difficulties in finding small objects from images.
- Diverse dataset training is required to attain optimal performance.
10 Best YOLO (You Only Look Once) Alternatives for Real-Time Object Detection in 2024
Human brains are powerful and can find objects in images with their visual system. It can perform complicated tasks like identifying objects and finding obstacles with ease. With vast amounts of data, quick GPUs, and better algorithms, the computers are now trained to detect and classify objects in an image accurately.
The objector detector will also count the number of objects in an image and track the location of it precisely while labeling it accurately. For instance, imagine a picture with two dogs and a single person. The object detection tool will scan through the image, classify the objects inside the image, and find examples. We have listed the ten YOLO Alternatives for Real-Time Object Detection.
10 Best YOLO (You Only Look Once) Alternatives for Real-Time Object Detection in 2024
- Top 10 Object Detection Tools in 2024
- TensorFlow
- Faster R-CNN (Region-based Convolutional Neural Network)
- EfficientDet
- RetinaNet
- Mask R-CNN
- CenterNet
- DETR
- Cascade R-CNN
- SSD
- FCOS
- Different Uses of Object Detection Models
- Conclusion
- FAQs – YOLO Alternatives for Real-Time Object Detection