Search Results for author:
Found 6 papers, 1 papers with code
On Characterizing the Evolution of Embedding Space of Neural Networks using Algebraic Topology
We study how the topology of feature embedding space changes as it passes through the layers of a well-trained deep neural network (DNN) through Betti numbers.
Altering Backward Pass Gradients improves Convergence
In standard neural network training, the gradients in the backward pass are determined by the forward pass.
DFCANet: Dense Feature Calibration-Attention Guided Network for Cross Domain Iris Presentation Attack Detection
To alleviate these shortcomings, this paper proposes DFCANet: Dense Feature Calibration and Attention Guided Network which calibrates the locally spread iris patterns with the globally located ones.
Cross-Domain Iris Presentation Attack Detection
Incremental Learning
+1
Sensor-invariant Fingerprint ROI Segmentation Using Recurrent Adversarial Learning
In order to save the human effort in generating annotations required by state-of-the-art, we propose a fingerprint roi segmentation model which aligns the features of fingerprint images derived from the unseen sensor such that they are similar to the ones obtained from the fingerprints whose ground truth roi masks are available for training.
Data Uncertainty Guided Noise-aware Preprocessing Of Fingerprints
The effectiveness of fingerprint-based authentication systems on good quality fingerprints is established long back.
High Accuracy Classification of Parkinson's Disease through Shape Analysis and Surface Fitting in $^{123}$I-Ioflupane SPECT Imaging
We use these features to develop and compare various classification models that can discriminate between scans showing dopaminergic deficit, as in PD, from scans without the deficit, as in healthy normal or SWEDD.
