Now IMAGIMOB Studio users can visualize their machine learning modeling workflows and leverage advanced capabilities to develop edge device models better and faster. Imagimob have launched the all-new Graph UX interface, designed to bring greater ease and clarity to the ML modeling process while offering advanced new capabilities such as built-in data collection and real-time model evaluation.
In line with their mission to offer the best and fastest ways to take smart devices to market, Imagimob is now launching IMAGIMOB Ready Models, complete machine learning solutions guaranteed to be robust, high-performing, and production-ready for edge devices. Ready Models can be quickly deployed onto existing MCU hardware without the cost, time, or expertise required for custom development.
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.
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.