This white paper explains what LSTM layers are, why they are important and what the technical solution in Imagimob AI looks like. In Imagimob AI, quantization of a pretrained model is done with the click of a button in a user-friendly graphical user interface, which generates C code without any floating-point operations, ready for deployment.
Imagimob today announced that its tinyML platform Imagimob AI supports quantization of so-called Long Short-Term Memory (LSTM) layers and a number of other TensorFlow layers. LSTM layers are well-suited to classify, process and make predictions based on time series data, and are therefore of great value when building tinyML applications.
As the pandemic has swept over the world, gesture control and touchless user interfaces have become a hot topic. Here, we’ll explore the different types of gesture control technologies and explain why we think radar technology powered by Edge AI stands out above the rest for certain use cases.
Imagimob has been part of an EU project, together with 55 companies and organisations throughout Europe, to investigate how Edge AI, aka tinyML and cloud services can support companies within connected agriculture; regarding both crop management and livestock.
Heute hat Imagimob bekannt gegeben, dass die neue Version seiner tinyML-Plattform ab sofort für seine Kunden verfügbar ist. Mit der neuen Version können Entwickler leichter und schneller einsatzbereite tinyML-Anwendungen auf Edge-Geräten erstellen und bereitstellen.
Imagimob today announced that the new release of its tinyML platform is now available to its customers. The new release focuses on making it easier and faster for developers to build and deploy performance-ready tinyML applications on edge devices.