Face Detection Using YOLO
Abhishek Rana · Zenodo (CERN European Organization for Nuclear Research) · 2022
Deep learning is a buzzword these days, and it’s a new phase of machine learning that teaches computers to detect patterns in enormous amounts of data. It primarily describes learning at several levels of representation, which aids in making understanding of text, voice, and visual data. Many businesses use a convolutional neural network, a sort of deep learning, to deal with the objects in a video sequence. Deep Convolution Neural Networks (CNNs) have demonstrated excellent performance in terms of object detection, picture classification, and semantic segmentation. Object detection is described as the process of classifying and locating objects. Face detection is one of the most difficult pattern recognition issues. Deep learning is a new phase of machine learning that teaches computers to find patterns in massive volumes of data, and it’s a buzzword these days. It mostly refers to learning at several levels of representation, which aids in the comprehension of text, audio, and visual data. To deal with the objects in a video sequence, many firms utilise a convolutional neural network, which is a type of deep learning. In terms of object detection, picture categorization, and semantic segmentation, Deep Convolution Neural Networks (CNNs) have shown to be quite effective. The process of classifying and locating things is referred to as object detection. One of the most difficult pattern recognition problems is face detection.