Low-power Design of a Gravity Rotation Module for HAR Systems Based on Inertial Sensors. - Antonio De Vita; Gian Domenico Licciardo; Luigi Di Benedetto; Danilo Pau; Emanuele Plebani; Angelo Bosco (ASAP, 2018)

µW Pre-processing Unit for Virtual Sensors Based on Tri-axial Smart Accelerometers. - Antonio De Vita; Gian Domenico Licciardo; Aldo Femia; Luigi Di Benedetto; Danilo Pau (NEWCAS, 2019)

A Bit-Line Voltage Sensing Circuit With Fused Offset Compensation and Cancellation Scheme. - Gian Domenico Licciardo; Luigi Di Benedetto; Antonio De Vita; Alfredo Rubino; Aldo Femia (IEEE Trans. Circuits Syst. II Express Briefs, 2019)

Low-Power HWAccelerator for AI Edge-Computing in Human Activity Recognition Systems. - Antonio De Vita; Danilo Pau; Claudio Parrella; Luigi Di Benedetto; Alfredo Rubino; Gian Domenico Licciardo (AICAS, 2020)

Low Power Tiny Binary Neural Network with improved accuracy in Human Recognition Systems. - Antonio De Vita; Danilo Pau; Luigi Di Benedetto; Alfredo Rubino; Frédéric Pétrot; Gian Domenico Licciardo (DSD, 2020)

Embeddable Circuit for Orientation Independent Processing in Ultra Low-Power Tri-Axial Inertial Sensors. - Antonio De Vita; Gian Domenico Licciardo; Aldo Femia; Luigi Di Benedetto; Alfredo Rubino; Danilo Pau (IEEE Trans. Circuits Syst. II Express Briefs, 2020)

A Partially Binarized Hybrid Neural Network System for Low-Power and Resource Constrained Human Activity Recognition. - Antonio De Vita; Alessandro Russo 006; Danilo Pau; Luigi Di Benedetto; Alfredo Rubino; Gian Domenico Licciardo (IEEE Trans. Circuits Syst., 2020)

Comparing Industry Frameworks with Deeply Quantized Neural Networks on Microcontrollers. - Danilo Pau; Marco Lattuada 001; Francesco Loro; Antonio De Vita; Gian Domenico Licciardo (ICCE, 2021)

Highly-accurate binary tiny neural network for low-power human activity recognition. - Antonio De Vita; Danilo Pau; Luigi Di Benedetto; Alfredo Rubino; Frédéric Pétrot; Gian Domenico Licciardo (Microprocess. Microsystems, 2021)

A 40-310TOPS/W SRAM-Based All-Digital Up to 4b In-Memory Computing Multi-Tiled NN Accelerator in FD-SOI 18nm for Deep-Learning Edge Applications. - Giuseppe Desoli; Nitin Chawla; Thomas Boesch; Manui Avodhyawasi; Harsh Rawat; Hitesh Chawla; VS Abhijith; Paolo Zambotti; Akhilesh Sharma; Carmine Cappetta; Michele Rossi; Antonio De Vita; et al. (ISSCC, 2023)