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A collection of 2 posts

Transfer Learning Part II: When to use them in Image Processing

Transfer learning allows you to leverage an existing model by modifying and retraining it to fulfill a new use case. In this blog, we explore some key scenarios for why and when you should choose transfer learning over building a new machine learning model from scratch for image processing.

Machine Learning

Using ResNets to Detect Anomalies in Industrial IoT Textile Production

Machine learning models for image classification often use convolutional neural networks (CNNs) to extract features from images while employing max-pooling layers to reduce dimensionality. The goal is to extract increasingly higher-level features from regions of the image, to ultimately make some kind of prediction such as an image classification. To