428 citations · 4.5k across the 191 of their papers we have counts for
7 papers · 1 filter
An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics
Francesco Conti, Robert Schilling, Pasquale Davide Schiavone +9
Near-sensor data analytics is a promising direction for IoT endpoints, as it minimizes energy spent on communication and reduces network load - but it also poses security concerns,…
CAS-CNN: A Deep Convolutional Neural Network for Image Compression Artifact Suppression
Lukas Cavigelli, Pascal Hager, Luca Benini
Lossy image compression algorithms are pervasively used to reduce the size of images transmitted over the web and recorded on data storage media. However, we pay for their high com…
Computationally Efficient Target Classification in Multispectral Image Data with Deep Neural Networks
Lukas Cavigelli, Dominic Bernath, Michele Magno +1
Detecting and classifying targets in video streams from surveillance cameras is a cumbersome, error-prone and expensive task. Often, the incurred costs are prohibitive for real-tim…
Deep Structured Features for Semantic Segmentation
Michael Tschannen, Lukas Cavigelli, Fabian Mentzer +2
We propose a highly structured neural network architecture for semantic segmentation with an extremely small model size, suitable for low-power embedded and mobile platforms. Speci…
A near-threshold RISC-V core with DSP extensions for scalable IoT Endpoint Devices
Michael Gautschi, Pasquale Davide Schiavone, Andreas Traber +6
Endpoint devices for Internet-of-Things not only need to work under extremely tight power envelope of a few milliwatts, but also need to be flexible in their computing capabilities…
YodaNN: An Architecture for Ultra-Low Power Binary-Weight CNN Acceleration
Renzo Andri, Lukas Cavigelli, Davide Rossi +1
Convolutional neural networks (CNNs) have revolutionized the world of computer vision over the last few years, pushing image classification beyond human accuracy. The computational…