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20222026
most citedEnergy-efficient Deployment of Deep Learning Applications on Cortex-M based Microcontrollers using Deep Compression

3 citations · 5 across the 4 of their papers we have counts for

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cs.LG2026

Rethinking Neural Nonlinearity as Gating

Muhammad Sabih, Frank Hannig, Jürgen Teich

Activation functions are considered an essential primitive for neural nonlinearity, i.e., they enable neural networks to serve as universal approximators. In this paper, we show th…

cs.AR2026

Co-Design of CNN Accelerators for TinyML using Approximate Matrix Decomposition

José Juan Hernández Morales, Georgios Mentzos, Frank Hannig +4

The paradigm shift towards local and on-device inference under stringent resource constraints is represented by the tiny machine learning (TinyML) domain. The primary goal of TinyM…