The MLOps Blog

FEBRUARY 22, 2024

TL;DR: In many machine-learning projects, the model has to frequently be retrained to adapt to changing data or to personalize it. Continual learning is a set of approaches to train machine learning models incrementally, using data samples only once as they arrive. What is continual learning?

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Viso.ai

APRIL 29, 2024

STNs are used to “teach” neural networks how to perform spatial transformations on input data to improve spatial invariance. Spatial Transformer Networks Explained The central component of the STN is the spatial transformer module. What’s Next for Spatial Transformer Networks?

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Viso.ai

MARCH 26, 2024

This enhances their ability to process sequences in tasks like robotic navigation and augmented reality applications. Attention Mechanisms in Deep Learning Attention mechanisms are helping reimagine both convolutional neural networks ( CNNs ) and sequence models.

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The MLOps Blog

APRIL 20, 2023

While convolutional neural networks (CNNs) are commonly used in smaller-scale facial recognition systems, scaling to a larger number of faces requires a more sophisticated approach. Edge deployment can be particularly useful in scenarios where real-time processing is essential, such as autonomous vehicles or robotics.

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Viso.ai

DECEMBER 21, 2023

From the development of sophisticated object detection algorithms to the rise of convolutional neural networks (CNNs) for image classification to innovations in facial recognition technology, applications of computer vision are transforming entire industries. Thus, positioning him as one of the top AI influencers in the world.

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