Classifying anomalies in images, that is assigning meaningful categories or descriptions to unexpected patterns, can automate quality control and enhance medical diagnostics. In this blog post, we... 更多内容 >>

For the past decade, AI has brought digital transformation from industrial automation, such as in visual inspection and predictive maintenance, to our everyday life. AI powers the search results we... 更多内容 >>

The following blog post is from Jack Ferrari, Edge AI Product Manager, Joe Sanford, Senior Application Engineer, and Reed Axman, Strategic Partner Manager. We recently attended the Edge AI... 更多内容 >>

As hospitals integrate more advanced patient monitoring systems, the ability to process, analyze, and act on real-time medical data has become critical. Traditional monitoring systems generate large... 更多内容 >>

MATLAB makes it easy to integrate Python®-based AI models into your MATLAB and Simulink workflows. You can call PyTorch® and TensorFlow™ models - or any Python code - directly from MATLAB. For... 更多内容 >>

In computer vision, pretrained models are often used and adapted to the task at hand by performing transfer learning. Transfer learning involves modifying and retraining a pretrained network with... 更多内容 >>

Deep neural networks like convolutional neural networks (CNNs) and long-short term memory (LSTM) networks can be applied for image- and sequence-based deep learning tasks. Graph neural networks... 更多内容 >>

Today is the last day of 2024. Most of you are busy with non-AI, non-programming, non-thinking-about-work preparations for the new year. Nevertheless, I wanted to wrap up this year by looking back... 更多内容 >>

As NeurIPS 2024 comes to a close, I am thinking back to all the inspiring presentations and conversations with brilliant AI researchers. It was clear that scientists are committed to bringing the... 更多内容 >>

In this previous blog post, we explored the key aspects and benefits of transformer models, described how you can use pretrained models with MATLAB, and promised a blog post that shows you how to... 更多内容 >>