40 citations · 41 across the 3 of their papers we have counts for
12 papers
Enhancing Fine-Grained Classification for Low Resolution Images
Maneet Singh, Shruti Nagpal, Mayank Vatsa +1
Low resolution fine-grained classification has widespread applicability for applications where data is captured at a distance such as surveillance and mobile photography. While fin…
On the Robustness of Face Recognition Algorithms Against Attacks and Bias
Richa Singh, Akshay Agarwal, Maneet Singh +2
Face recognition algorithms have demonstrated very high recognition performance, suggesting suitability for real world applications. Despite the enhanced accuracies, robustness of…
Dual Directed Capsule Network for Very Low Resolution Image Recognition
Maneet Singh, Shruti Nagpal, Richa Singh +1
Very low resolution (VLR) image recognition corresponds to classifying images with resolution 16x16 or less. Though it has widespread applicability when objects are captured at a v…
Deep Learning for Face Recognition: Pride or Prejudiced?
Shruti Nagpal, Maneet Singh, Richa Singh +1
Do very high accuracies of deep networks suggest pride of effective AI or are deep networks prejudiced? Do they suffer from in-group biases (own-race-bias and own-age-bias), and mi…
Supervised COSMOS Autoencoder: Learning Beyond the Euclidean Loss!
Maneet Singh, Shruti Nagpal, Mayank Vatsa +2
Autoencoders are unsupervised deep learning models used for learning representations. In literature, autoencoders have shown to perform well on a variety of tasks spread across mul…
Learning A Shared Transform Model for Skull to Digital Face Image Matching
Maneet Singh, Shruti Nagpal, Richa Singh +2
Human skull identification is an arduous task, traditionally requiring the expertise of forensic artists and anthropologists. This paper is an effort to automate the process of mat…