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  1. Article

    Open Access

    DeConFuse: a deep convolutional transform-based unsupervised fusion framework

    This work proposes an unsupervised fusion framework based on deep convolutional transform learning. The great learning ability of convolutional filters for data analysis is well acknowledged. The success of co...

    Pooja Gupta, Jyoti Maggu, Angshul Majumdar… in EURASIP Journal on Advances in Signal Proc… (2020)

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  2. No Access

    Chapter and Conference Paper

    Deep Convolutional Transform Learning

    This work introduces a new unsupervised representation learning technique called Deep Convolutional Transform Learning (DCTL). By stacking convolutional transforms, our approach is able to learn a set of indep...

    Jyoti Maggu, Angshul Majumdar, Emilie Chouzenoux… in Neural Information Processing (2020)

  3. No Access

    Chapter and Conference Paper

    Semi-coupled Transform Learning

    This work introduces semi-coupled transform learning. Given training data in two domains (source and target), it learns a transform in each of the domains such that the corresponding coefficients are (linearl...

    Jyoti Maggu, Angshul Majumdar in Neural Information Processing (2018)

  4. No Access

    Chapter and Conference Paper

    Convolutional Transform Learning

    This work proposes a new representation learning technique called convolutional transform learning. In standard transform learning, a dense basis is learned that analyses the image to generate the representati...

    Jyoti Maggu, Emilie Chouzenoux, Giovanni Chierchia… in Neural Information Processing (2018)