output
20132024
most citedEffectiveness of Scaled Exponentially-Regularized Linear Units (SERLUs)

5 citations

5 papers

cs.AR2024★ 1 cited

Teaching Experiences using the RVfpga Package

D. Chaver, S. Harris, L. Pinuel +13

The RVfpga course offers a solid introduction to computer architecture using the RISC-V instruction set and FPGA technology. It focuses on providing hands-on experience with real-w…

cs.CV2019★ 3 cited

Object Detection and 3D Estimation via an FMCW Radar Using a Fully Convolutional Network

Guoqiang Zhang, Haopeng Li, Fabian Wenger

This paper considers object detection and 3D estimation using an FMCW radar. The state-of-the-art deep learning framework is employed instead of using traditional signal processing…

cs.LG2018★ 5 cited

Effectiveness of Scaled Exponentially-Regularized Linear Units (SERLUs)

G. Zhang, H. Li

Recently, self-normalizing neural networks (SNNs) have been proposed with the intention to avoid batch or weight normalization. The key step in SNNs is to properly scale the expone…

cs.IT2015

Broadcast Coded Slotted ALOHA: A Finite Frame Length Analysis

Mikhail Ivanov, Fredrik Brannstrom, Alexandre Graell i Amat +1

We propose an uncoordinated medium access control (MAC) protocol, called all-to-all broadcast coded slotted ALOHA (B-CSA) for reliable all-to-all broadcast with strict latency cons…

cs.IT2013

A Low-Complexity Detector for Memoryless Polarization-Multiplexed Fiber-Optical Channels

Christian Häger, Lotfollah Beygi, Erik Agrell +3

A low-complexity detector is introduced for polarization-multiplexed M-ary phase shift keying modulation in a fiber-optical channel impaired by nonlinear phase noise, generalizing…