12 citations · 40 across the 18 of their papers we have counts for
5 papers · 1 filter
Heterogeneous graphs model spatial relationships between biological entities for breast cancer diagnosis
Akhila Krishna K, Ravi Kant Gupta, Nikhil Cherian Kurian +2
The heterogeneity of breast cancer presents considerable challenges for its early detection, prognosis, and treatment selection. Convolutional neural networks often neglect the spa…
WaveMixSR: A Resource-efficient Neural Network for Image Super-resolution
Pranav Jeevan, Akella Srinidhi, Pasunuri Prathiba +1
Image super-resolution research recently been dominated by transformer models which need higher computational resources than CNNs due to the quadratic complexity of self-attention.…
WavePaint: Resource-efficient Token-mixer for Self-supervised Inpainting
Pranav Jeevan, Dharshan Sampath Kumar, Amit Sethi
Image inpainting, which refers to the synthesis of missing regions in an image, can help restore occluded or degraded areas and also serve as a precursor task for self-supervision.…
CHATTY: Coupled Holistic Adversarial Transport Terms with Yield for Unsupervised Domain Adaptation
Chirag P, Mukta Wagle, Ravi Kant Gupta +2
We propose a new technique called CHATTY: Coupled Holistic Adversarial Transport Terms with Yield for Unsupervised Domain Adaptation. Adversarial training is commonly used for lear…
Magnification Invariant Medical Image Analysis: A Comparison of Convolutional Networks, Vision Transformers, and Token Mixers
Pranav Jeevan, Nikhil Cherian Kurian, Amit Sethi
Convolution Neural Networks (CNNs) are widely used in medical image analysis, but their performance degrade when the magnification of testing images differ from the training images…