Search Results - "Canese, Lorenzo"

Multi-Agent Reinforcement Learning: A Review of Challenges and Applications by Canese, Lorenzo, Cardarilli, Gian Carlo, Di Nunzio, Luca, Fazzolari, Rocco, Giardino, Daniele, Re, Marco, Spanò, Sergio

“…In this review, we present an analysis of the most used multi-agent reinforcement learning algorithms. Starting with the single-agent reinforcement learning…”
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Resilient multi-agent RL: introducing DQ-RTS for distributed environments with data loss by Canese, Lorenzo, Cardarilli, Gian Carlo, Di Nunzio, Luca, Fazzolari, Rocco, Re, Marco, Spanò, Sergio

“…This paper proposes DQ-RTS, a novel decentralized Multi-Agent Reinforcement Learning algorithm designed to address challenges posed by non-ideal communication…”
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Sensing and Detection of Traffic Signs Using CNNs: An Assessment on Their Performance by Canese, Lorenzo, Cardarilli, Gian Carlo, Di Nunzio, Luca, Fazzolari, Rocco, Famil Ghadakchi, Hamed, Re, Marco, Spanò, Sergio

“…Traffic sign detection systems constitute a key component in trending real-world applications such as autonomous driving and driver safety and assistance. In…”
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Design Space Exploration for Edge Machine Learning Featured by MathWorks FPGA DL Processor: A Survey by Bertazzoni, Stefano, Canese, Lorenzo, Cardarilli, Gian Carlo, Nunzio, Luca Di, Fazzolari, Rocco, Re, Marco, Spano, Sergio

“…This paper proposes a Design Space Exploration for Edge machine learning through the utilization of the novel MathWorks FPGA Deep Learning Processor IP,…”
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A Novel Digital Equalizer Based on RF Sampling Beyond GHz by Canese, Lorenzo, Carlo Cardarilli, Gian, Cesa, Riccardo la, Di Nunzio, Luca, Fazzolari, Rocco, Giardino, Daniele, Re, Marco, Spano, Sergio

“…Hardware implementations represent the major challenges when digital signal processors for ultra-wideband (UWB) signals must be developed. Due to the…”
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A Hardware-Oriented QAM Demodulation Method Driven by AW-SOM Machine Learning by Canese, Lorenzo, Cardarilli, Gian Carlo, Di Nunzio, Luca, Fazzolari, Rocco, Re, Marco, Spano, Sergio

“…We propose a QAM demodulator based on the AWSOM (All Winner SOM), a clustering algorithm optimized for efficient hardware implementation. The demodulator has…”
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Profiling of CNNs using the MATLAB FPGA-based Deep Learning Processor by Spano, Sergio, Canese, Lorenzo, Cardarilli, Gian Carlo

“…In this paper we assess the performance of the new MATLAB Deep Learning Processor. It is a hardware architecture meant for FPGA devices which is able to infer…”
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