top of page

W4: Towards Self Contained Recognition
Integrated Classifiers for Smart Sensors





Half day, 13:30 - 18:00



Room 5


Classifiers such as Neural Networks have become ubiquitous solutions when complex classification tasks are at stake, while hybridization and CMOS processing capabilities have paved the way towards fully integrated sensors. Not surprisingly, the convergence of the two worlds in now on but poses complex challenges: among them compactness, low power consumption and high classification ratio. This workshop aims at proving an overview of the challenges of integrated NN design, technological solutions and use cases.


Antoine Dupret (CEA-Leti, FR)

Cedric Tubert (STMicroelectronics, FR)


Integrated Neural Networks, the challenge of featuring versatility and compactness

Jerome Chossat (STMicroelectronics, FR)


Algorithm-Architecture co-design for highly constrained, application-oriented deep learning models

William Guicquero (CEA-Leti, FR)


Bio inspired: event driven sensors and spiking NN

Chang Gao (TU Delft, NL)


In-memory Computing for Sensor-rich Edge Platforms

Naveen Verma (Princeton University, US)


Ultra-Low Power Sensing Systems for Artificial Intelligence of Things (AIoT)

Dennis Sylvester (University of Michigan, US)


Analog Acceleration: the next enabler?

Piotr Dudek (University of Manchester, UK)

bottom of page