We have received acceptance for a paper entitled "ALF: Autoencoder-based Low-rank Filter-sharing for Efficient Convolutional Neural Networks", authored by Alexander Frickenstein, Manoj-Rohit Vemparala, Nael Fasfous, Laura Hauenschild, Naveen-Shankar Nagaraja, Christian Unger, and Walter Stechele. In this paper, the authors propose an autoencoder-based pruning method for Convolutional Neural Networks, considering computational and memory restrictions on embedded platforms.

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