coreylammie/Low-Power-and-High-Speed-Deep-FPGA-Inference-Engines-for-Weed-Classification

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coreylammie/Low-Power-and-High-Speed-Deep-FPGA-Inference-Engines-for-Weed-Classification

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IEEE Access: Low-Power and High-Speed Deep FPGA Inference Engines for Weed Classification at the Edge

MemTorch

A Simulation Framework for Memristive Deep Learning Systems

TCAS-STDP

IEEE Transactions on Circuits and Systems I: Efficient FPGA Implementations of Pair and Triplet-based STDP for Neuromorphic Architectures

Memristive-Seizure-Detection-and-Prediction-by-Parallel-Convolutional-Neural-Networks

IEEE Transactions on Biomedical Circuits and Systems: Memristive Seizure Detection and Prediction by Parallel Convolutional Neural Networks

Jupyter Notebook

Accelerating-Stochastically-Binarized-Neural-Networks-on-FPGAs-using-OpenCL

2019 IEEE International Midwest Symposium on Circuits and Systems: Accelerating Stochastically Binarized Neural Networks on FPGAs using OpenCL

TBCAS-Towards-Healthcare-and-Biomedical-Applications

IEEE Transactions on Biomedical Circuits and Systems: Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications

Modeling-and-Simulating-In-Memory-Memristive-Deep-Learning-Systems

Array: Modeling and Simulating In-Memory Memristive Deep Learning Systems: An Overview of Current Efforts

SST-Reproducibility

IOP Semiconductor Science and Technology: Empirical Metal-Oxide RRAM Device Endurance and Retention Model for Deep Learning Simulations