Elenco Pubblicazioni - Publications (1546)
V. S. Raghavan, D. Kanoulas, D. G. Caldwell and N. G. Tsagarakis, "Reconfigurable and Agile Legged-Wheeled Robot Navigation in Cluttered Environments With Movable Obstacles," in IEEE Access, vol. 10, pp. 2429-2445, 2022, doi: 10.1109/ACCESS.2021.3139
Written by VIGNESH SUSHRUTHA RAGHAVAN
Abstract: Legged and wheeled locomotion are two standard methods used by robots to perform navigation. Combining them to create a hybrid legged-wheeled locomotion results in increased speed, agility, and reconfigurability for the robot, allowing it…
M. Cococcioni, F. Rossi, E. Ruffaldi, S. Saponara, "Small reals representations for Deep Learning at the edge: a comparison", Conference on Next Generation Arithmetic (CoNGA'22)
Written by FEDERICO ROSSI
Abstract: The pervasiveness of deep neural networks (DNNs) in edge devices enforced new requirements on information representation. Low precision format from 16 bits down to 1 or 2 bits have been proposed in the last…
M. Cococcioni, F. Rossi, E. Ruffaldi, S. Saponara, "Experimental Results of Vectorized Posit-Based DNNs on a Real ARM SVE High Performance Computing Machine", ApplePies 2021
Written by FEDERICO ROSSI
Abstract: With the pervasiveness of deep neural networks in scenarios that bring real-time requirements, there is the increasing need for optimized arithmetic on high performance architectures. In this paper we adopt two key visions: i)…
E. Rapuano, T. Pacini, L. Fanucci - "A Post-training Quantization Method for the Design of Fixed-Point-Based FPGA/ASIC Hardware Accelerators for LSTM/GRU Algorithms", Hindawi Computational Intelligence and Neuroscience journal, 11 May 2022
Written by EMILIO RAPUANO
Recurrent Neural Networks (RNNs) have become important tools for tasks such as speech recognition, text generation, or natural language processing. However, their inference may involve up to billions of operations and their large number of…
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