1 code implementation • 17 Mar 2023 • Chen Li, Edward Jones, Steve Furber
In this regard, Dynamic Confidence represents a meaningful step toward realizing the potential of SNNs.
no code implementations • 24 Feb 2023 • Arindam Das, Sudip Das, Ganesh Sistu, Jonathan Horgan, Ujjwal Bhattacharya, Edward Jones, Martin Glavin, Ciarán Eising
Multimodal learning, particularly for pedestrian detection, has recently received emphasis due to its capability to function equally well in several critical autonomous driving scenarios such as low-light, night-time, and adverse weather conditions.
no code implementations • 15 Jun 2022 • Arindam Das, Sudip Das, Ganesh Sistu, Jonathan Horgan, Ujjwal Bhattacharya, Edward Jones, Martin Glavin, Ciarán Eising
The proposed framework has improved state-of-the-art performances of pose estimation, pedestrian detection, and instance segmentation.
Ranked #18 on Pose Estimation on COCO test-dev
2 code implementations • 20 May 2022 • Shane Gilroy, Darragh Mullins, Edward Jones, Ashkan Parsi, Martin Glavin
Accurate detection and classification of vulnerable road users is a safety critical requirement for the deployment of autonomous vehicles in heterogeneous traffic.
no code implementations • 11 May 2022 • Shane Gilroy, Martin Glavin, Edward Jones, Darragh Mullins
Pedestrian detection is among the most safety-critical features of driver assistance systems for autonomous vehicles.
2 code implementations • 10 May 2022 • Shane Gilroy, Darragh Mullins, Edward Jones, Ashkan Parsi, Martin Glavin
RetinaNet has the lowest overall detection performance across the range of occlusion levels.
no code implementations • 24 Feb 2021 • Xiaoyu Huang, Edward Jones, Siru Zhang, Shouyu Xie, Steve Furber, Yannis Goulermas, Edward Marsden, Ian Baistow, Srinjoy Mitra, Alister Hamilton
This paper details the FPGA implementation methodology for Convolutional Spiking Neural Networks (CSNN) and applies this methodology to low-power radioisotope identification using high-resolution data.
no code implementations • 25 Oct 2020 • Xiaoyu Huang, Edward Jones, Siru Zhang, Shouyu Xie, Steve Furber, Yannis Goulermas, Edward Marsden, Ian Baistow, Srinjoy Mitra, Alister Hamilton
this paper presents a detailed methodology of a Spiking Neural Network (SNN) based low-power design for radioisotope identification.
no code implementations • 11 Jul 2020 • Xiaoyu Huang, Edward Jones, Siru Zhang, Steve Furber, Yannis Goulermas, Edward Marsden, Ian Baistow, Srinjoy Mitra, Alister Hamilton
This paper identifies the problem of unnecessary high power overhead of the conventional frame-based radioisotope identification process and proposes an event-based signal processing process to address the problem established.