355 citations · 980 across the 44 of their papers we have counts for
6 papers · 1 filter
Design Automation for Binarized Neural Networks: A Quantum Leap Opportunity?
Manuele Rusci, Lukas Cavigelli, Luca Benini
Design automation in general, and in particular logic synthesis, can play a key role in enabling the design of application-specific Binarized Neural Networks (BNN). This paper pres…
Hydra: An Accelerator for Real-Time Edge-Aware Permeability Filtering in 65nm CMOS
Manuel Eggimann, Christelle Gloor, Florian Scheidegger +4
Many modern video processing pipelines rely on edge-aware (EA) filtering methods. However, recent high-quality methods are challenging to run in real-time on embedded hardware due…
Chipmunk: A Systolically Scalable 0.9 mm, 3.08 Gop/s/mW @ 1.2 mW Accelerator for Near-Sensor Recurrent Neural Network Inference
Francesco Conti, Lukas Cavigelli, Gianna Paulin +2
Recurrent neural networks (RNNs) are state-of-the-art in voice awareness/understanding and speech recognition. On-device computation of RNNs on low-power mobile and wearable device…
Efficient Convolutional Neural Network For Audio Event Detection
Matthias Meyer, Lukas Cavigelli, Lothar Thiele
Wireless distributed systems as used in sensor networks, Internet-of-Things and cyber-physical systems, impose high requirements on resource efficiency. Advanced preprocessing and…
CBinfer: Change-Based Inference for Convolutional Neural Networks on Video Data
Lukas Cavigelli, Philippe Degen, Luca Benini
Extracting per-frame features using convolutional neural networks for real-time processing of video data is currently mainly performed on powerful GPU-accelerated workstations and…
Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations
Eirikur Agustsson, Fabian Mentzer, Michael Tschannen +4
We present a new approach to learn compressible representations in deep architectures with an end-to-end training strategy. Our method is based on a soft (continuous) relaxation of…