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• W2734679871 abstract "Image features can be learned and subsequently used for reconstruction and classification tasks in the fields of machine learning and computer vision. In this work, we propose image reconstruction using Convolutional Sparse Coding (CSC) on IBM's TrueNorth Neuromorphic computing system. CSC explicitly models local interactions through the convolution operations. Convolutional kernels define a dictionary and Sparse Feature Maps (SFMs) that are generated through a training process. The images are reconstructed with convolutional operations on SFMs and respective kernels. In this paper, we report on experimental results demonstrating promising sparse reconstructions on the IBM Neuromorphic TrueNorth hardware for two different benchmarks: MNIST and CIFAR-10. It is noted that this is the first ever important step towards convolutional sparse coding on neuromorphic hardware." @default.
• W2734679871 created "2017-07-21" @default.
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• W2734679871 date "2017-05-01" @default.
• W2734679871 modified "2023-09-22" @default.
• W2734679871 title "Convolutional sparse coding on neurosynaptic cognitive system" @default.
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• W2734679871 doi "https://doi.org/10.1109/ijcnn.2017.7966310" @default.
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