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05/20/2023
A request for clarity over the End of Sequence token in the Self-Critical Sequence Training
The Image Captioning research field is currently compromised by the lack...
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11/27/2022
HULK-V: a Heterogeneous Ultra-low-power Linux capable RISC-V SoC
IoT applications span a wide range in performance and memory footprint, ...
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08/13/2022
ExpansionNet v2: Block Static Expansion in fast end to end training for Image Captioning
Expansion methods explore the possibility of performance bottlenecks in ...
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10/20/2021
A TinyML Platform for On-Device Continual Learning with Quantized Latent Replays
In the last few years, research and development on Deep Learning models ...
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08/12/2020
Leveraging Automated Mixed-Low-Precision Quantization for tiny edge microcontrollers
The severe on-chip memory limitations are currently preventing the deplo...
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07/22/2020
Memory-Latency-Accuracy Trade-offs for Continual Learning on a RISC-V Extreme-Edge Node
AI-powered edge devices currently lack the ability to adapt their embedd...
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07/01/2020
Robust navigation with tinyML for autonomous mini-vehicles
Autonomous navigation vehicles have rapidly improved thanks to the break...
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05/30/2019
Memory-Driven Mixed Low Precision Quantization For Enabling Deep Network Inference On Microcontrollers
This paper presents a novel end-to-end methodology for enabling the depl...
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12/18/2017
HERO: Heterogeneous Embedded Research Platform for Exploring RISC-V Manycore Accelerators on FPGA
Heterogeneous embedded systems on chip (HESoCs) co-integrate a standard ...
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12/04/2017
