What are the trade-offs between model accuracy and interpretability?

Image classification is the simplest of the three tasks and involves classifying an entire image into one of a set of predefined classes. Deploy Image Processing Inference pipeline with InferenceGraph¶. The tutorial demonstrates how to deploy an image processing inference pipeline with ... Dec 11, 2024 ... We propose digital-analog quantum kernels for enhancing the detection of complex features in the classification of images. Jan 14, 2022 ... SEDC is introduced as a model-agnostic instance-level explanation method for image classification that does not need access to the training data. Apr 11, 2025 ... This preview model is a retrainable deep learning model used to classify images. You can train it on your own data and create an ML Skill to ... Image classification refers to the task of assigning classes—defined in a land cover and land use classification system, known as the schema—to all the pixels ... Jul 18, 2022 ... Image classification is a supervised learning problem: define a set of target classes (objects to identify in images), and train a model to ... Image classification is the process of categorizing and labeling groups of pixels or vectors within an image based on specific rules. Segmentation is another type of labeling where each pixel in an image is labeled with given concepts, providing pixel-by-pixel details for a given object. Image ... Image recognition is the process of identifying an object or a feature in an image or video. It is used in many applications like defect detection, medical ...