''Extreme edge” devices, such as smart sensors, are a uniquely challenging environment for
the deployment of machine learning. The tiny energy budgets of these devices lie beyond …

Abstract Weightless Neural Networks (WNN) are ideal for Federated Learning due to their
robustness and computational efficiency. These scenarios require models with a small …

Logic Neural Networks (LNNs) represent a new paradigm for implementing neural networks
in hardware devices such as Field-Programmable Gate Arrays (FPGAs). These network …

With the advent of Internet-of-Things (IoT) and edge computing devices, there has been an
increased demand for low power and high-throughput machine learning inference on the …

This paper presents a method to perform the real-time creation of models that are used to
represent aspects of tracked objects in video frames. Object modeling is done during the …

Thermal treatments that use ultrasound devices as a tool have as a key point the
temperature control to be applied in a specific region of the patient's body. This kind of …

Tire pressure monitoring system (TPMS) has a critical role in safeguarding vehicle safety by
monitoring tire pressure levels. Keeping the accurate tire pressure is necessary for …

As Deep Neural Networks become more complex and computationally demanding, efficient
models for inference at the edge, particularly multiplication-free ones, have gained …

The binary encoding of real valued inputs is a crucial part of Weightless Neural Networks.
The Linear Thermometer and its variations are the most prominent methods to determine …

Mimicking biological neurons by focusing on the excitatory/inhibitory decoding performed by
dendritic trees offers an intriguing alternative to the traditional integrate-and-fire McCullogh …