Keras CIFAR 10 Vision App for Image Classification using Tensorflow #tinyml #edge #nocodeplatform

Did you know that AI in the computer vision market is projected to reach USD 51.3 billion by 2026, at a CAGR of 26.3%. Computer vision is used to detect and classify objects (e.g., road signs or traffic lights), create 3D maps or motion estimation, and it plays a key role in making autonomous vehicles a reality.
Now computer vision applications can be made to run on tinyML devices like microcontrollers connected with a small camera like arducam with image classification of over 99% and a processing time of just milliseconds. The rest of this video outlines how to use the TinyML Vision classification technology to classify images.

cAInvas is built on no-code, low-code and full-code principles for AI applications and models derived from all popular platform like TensorFlow, keras, PyTorch and others.

cAInvas is bolstered by native integration of deepC inference framework and a compiler designed for embedded devices. It comes with python and c++ notebooks to develop end-to-end application with autoML and ensemble of ML models.

Best of all, it is free for all students, researchers and hobbyists to spread fast adoption of ML models for tiny devices. Reach out for more information: