Corey Lammie
Title
Cited by
Cited by
Year
Low-Power and High-Speed Deep FPGA Inference Engines for Weed Classification at the Edge.
C Lammie, A Olsen, T Carrick, MR Azghadi
IEEE Access 7, 51171-51184, 2019
312019
Hardware implementation of deep network accelerators towards healthcare and biomedical applications
MR Azghadi, C Lammie, JK Eshraghian, M Payvand, E Donati, ...
IEEE Transactions on Biomedical Circuits and Systems 14 (6), 1138-1159, 2020
232020
Efficient FPGA implementations of pair and triplet-based STDP for neuromorphic architectures
C Lammie, TJ Hamilton, A van Schaik, MR Azghadi
IEEE Transactions on Circuits and Systems I: Regular Papers 66 (4), 1558-1570, 2018
222018
Unsupervised Character Recognition with a Simplified FPGA Neuromorphic System
C Lammie, T Hamilton, MR Azghadi
Circuits and Systems (ISCAS), 2018 IEEE International Symposium on, 1-5, 2018
152018
Variation-aware binarized memristive networks
C Lammie, O Krestinskaya, A James, MR Azghadi
2019 26th IEEE International Conference on Electronics, Circuits and Systems …, 2019
62019
Accelerating deterministic and stochastic binarized neural networks on FPGAS using OpenCL
C Lammie, W Xiang, MR Azghadi
2019 IEEE 62nd International Midwest Symposium on Circuits and Systems …, 2019
62019
MemTorch: A simulation framework for deep memristive Cross-Bar architectures
C Lammie, MR Azghadi
2020 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2020
52020
MemTorch: An open-source simulation framework for memristive deep learning systems
C Lammie, W Xiang, B Linares-Barranco, MR Azghadi
arXiv preprint arXiv:2004.10971, 2020
52020
Stochastic computing for low-power and high-speed deep learning on FPGA
C Lammie, MR Azghadi
2019 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2019
52019
Empirical metal-oxide RRAM device endurance and retention model for deep learning simulations
C Lammie, MR Azghadi, D Ielmini
Semiconductor Science and Technology 36 (6), 065003, 2021
32021
Training progressively binarizing deep networks using FPGAs
C Lammie, W Xiang, MR Azghadi
2020 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2020
32020
Memristive Stochastic Computing for Deep Learning Parameter Optimization
C Lammie, JK Eshraghian, WD Lu, MR Azghadi
IEEE Transactions on Circuits and Systems II: Express Briefs 68 (5), 1650-1654, 2021
22021
Live demonstration: Unsupervised character recognition with a FPGA neuromorphic system
C Lammie, T Hamilton, MR Azghadi
2018 IEEE International Symposium on Circuits and Systems (ISCAS), 1-1, 2018
22018
Towards Memristive Deep Learning Systems for Real-time Mobile Epileptic Seizure Prediction
C Lammie, W Xiang, MR Azghadi
2021 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2021
12021
A Deep Learning Localization Method for Measuring Abdominal Muscle Dimensions in Ultrasound Images
A Saleh, IH Laradji, C Lammie, D Vazquez, CA Flavell, MR Azghadi
IEEE Journal of Biomedical and Health Informatics, 2021
2021
Biologically plausible contrast detection using a memristor array
JK Eshraghian, C Lammie, MR Azghadi
2020 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2020
2020
Live Demonstration: Low-Power and High-Speed Deep FPGA Inference Engines for Weed Classification at the Edge
C Lammie, MR Azghadi
2020 IEEE International Symposium on Circuits and Systems (ISCAS), 1-1, 2020
2020
Digital, analog, and memristive implementation of Spike-based Synaptic Plasticity
M Lammie, Corey, and Rahimiazghadi
SCiNDU: Systems & Computational Neuroscience Down Under, 46, 2017
2017
SPECIAL SECTION ON THE 2020 IEEE INTERNATIONAL SOLID-STATE CIRCUITS CONFERENCE
MR Azghadi, C Lammie, JK Eshraghian, M Payvand, E Donati, ...
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Articles 1–19