We have installed AI models on Raspberry Pi locally including tinyllama, Microsoft's Phi model, and smollm.

In this context, achieving accurate target detection of brain tumors in MRI images becomes particularly important as it can improve the timeliness of diagnosis and the effectiveness of treatment. To ...

Conclusion Exploring machine learning with TensorFlow on Ubuntu opens a world of possibilities. Whether you're a beginner or an experienced practitioner, the combination of TensorFlow's powerful ...

The proposed model has four main steps, namely, preprocessing, segmentation, feature extraction, and classification. Initially, the input SAR image is pre-processed using a histogram equalization ...

With the growth of the Internet of Things, we see an increase in the importance of analysis of data from the edge, often with the results needed in real-time. Indy Car series is one of the well-known ...

This guide provides step-by-step instructions for how train a custom TensorFlow Object Detection model, convert it into an optimized format that can be used by TensorFlow Lite, and run it on edge ...

There are four Python scripts to run the TensorFlow Lite object detection model on an image, video, web stream, or webcam feed. The scripts are based off the label_image.py example given in the ...