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Found 5 papers, 5 papers with code
Human Hands as Probes for Interactive Object Understanding
Analyzing the hands shows what we can do to objects and how.
DZip: improved general-purpose lossless compression based on novel neural network modeling
We propose DZip, a general-purpose compressor for sequential data that exploits the well-known modeling capabilities of neural networks (NNs) for prediction, followed by arithmetic coding.
Learning Activation Functions: A new paradigm for understanding Neural Networks
Since the optimization of SLNNs is still a challenge, we show that using SLAF along with standard activations (like ReLU) can provide performance improvements with only a small increase in number of parameters.
DeepZip: Lossless Data Compression using Recurrent Neural Networks
We combine recurrent neural network predictors with an arithmetic coder and losslessly compress a variety of synthetic, text and genomic datasets.
Detection of Glottal Closure Instants using Deep Dilated Convolutional Neural Networks
Most of the existing approaches for GCI detection adopt a two-stage approach - (i) Transformation of speech signal into a representative signal where GCIs are localized better, (ii) extraction of GCIs using the representative signal obtained in first stage.
Sound Audio and Speech Processing
