Computer vision terms
Object detection algorithms
Histogram of Oriented Gradients (HOG) → Introduction. Region-based Convolutional Neural Networks (R-CNN) → Introduction. Faster R-CNN. → Introduction. Single Shot Detector (SSD) → Introduction. YOLO (You Only Look Once) → Introduction. RetinaNet. → Introduction. ImageAI. → Introduction. GluonCV..How do you create a computer vision algorithm?
The newest YOLO algorithm surpasses all previous object detection models and YOLO versions in both speed and accuracy.
It requires several times cheaper hardware than other neural networks and can be trained much faster on small datasets without any pre-trained weights..
What algorithms does computer vision use?
Computer vision applications use artificial intelligence and machine learning (AI/ML) to process this data accurately for object identification and facial recognition, as well as classification, recommendation, monitoring, and detection..
What is the fastest computer vision algorithm?
Deep Belief Networks (DBNs)
Deep Belief Networks (DBNs) are used for image-recognition, video-recognition, and motion-capture data..
Which algorithm is used in video recognition?
Compared to traditional computer vision algorithms, deep learning makes it possible to achieve greater accuracy in extremely complex tasks such as image classification, object detection, semantic segmentation, and Simultaneous Localization and Mapping (SLAM)..
Why is deep learning a suitable algorithm for computer vision?
Compared to traditional computer vision algorithms, deep learning makes it possible to achieve greater accuracy in extremely complex tasks such as image classification, object detection, semantic segmentation, and Simultaneous Localization and Mapping (SLAM)..
