81 citations
- STMicroelectronics (Czechia)CZ6 papers
- Centre National de la Recherche ScientifiqueFR4 papers
- STMicroelectronics (Italy)IT4 papers
- Institut d'électronique de microélectronique et de nanotechnologieFR2 papers
- STMicroelectronics (France)FR2 papers
- BreakthroughUS1 paper
- CEA GrenobleFR1 paper
- Centre de Nanosciences et de NanotechnologiesFR1 paper
- Centre de Radiofréquences, Optique et Micro-nanoélectronique des AlpesFR1 paper
- Centre Hospitalier Sud FrancilienFR1 paper
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- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR1 paper
13 papers
Enhanced selfphase modulation in silicon nitride waveguides with integrated 2D MoS2 films
Shahaz S. Hameed, Di Jin, Aihao Zhao +9
On-chip integration of 2D materials provides a promising route towards next-generation integrated optical devices with performance beyond existing limits. Here, significantly enhan…
OASI: Objective-Aware Surrogate Initialization for Multi-Objective Bayesian Optimization in TinyML Keyword Spotting
Soumen Garai, Danilo Pau, Suman Samui
Voice-triggered interfaces rely on keyword spotting (KWS) models that must operate continuously under strict memory, latency, and energy constraints on microcontroller-class hardwa…
Adaptive Extended Kalman Filtering for Battery State of Charge Estimation on STM32
António Barros, Edoardo Peretti, Davide Fabroni +3
Accurate and computationally light algorithms for estimating the State of Charge (SoC) of a battery's cells are crucial for effective battery management on embedded systems. In thi…
Three-dimensional broadband FDTD optical simulations of CMOS image sensor
A. Crocherie, Jérôme Vaillant, F. Hirigoyen
In this paper, we present the results of rigorous electromagnetic broadband simulations applied to CMOS image sensors as well as experimental measurements. We firstly compare the r…
MLPerf Tiny Benchmark
Colby Banbury, Vijay Janapa Reddi, Peter Torelli +19
Advancements in ultra-low-power tiny machine learning (TinyML) systems promise to unlock an entirely new class of smart applications. However, continued progress is limited by the…
Charge-Based Compact Model for Bias-Dependent Variability of 1/f Noise in MOSFETs
Nikolaos Mavredakis, Nikolaos Makris, Predrag Habas +1
Variability of low frequency noise (LFN) in MOSFETs is bias-dependent. Moderate- to large-sized transistors commonly used in analog/RF applications show 1/f-like noise spectra, res…