Convolutional Neural Network (CNN)


In deep learning, a convolutional neural network (CNN) is a type of artificial neural network commonly used for processing and analyzing visual imagery recognition. Compared with traditional neural networks, CNNs are more effective and efficient for image processing and natural language processing because they are specifically designed to analyze pixel data. Applications of CNNs include different computer vision tasks such as image and video recognition, image classification, image segmentation, and medical image analysis, as well as time series and brain-computer interfaces.



Here’s an architecture of a ResNet family, an example of a CNN for image classification. Read the blog for an overview of SOTA deep neural networks.

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					from transformers import AutoFeatureExtractor, AutoModelForImageClassification

extractor = AutoFeatureExtractor.from_pretrained("microsoft/resnet-50")

model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-50")