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Found 9 papers, 1 papers with code
A Novel Sector-Based Algorithm for an Optimized Star-Galaxy Classification
This paper introduces a novel sector-based methodology for star-galaxy classification, leveraging the latest Sloan Digital Sky Survey data (SDSS-DR18).
MD-CSDNetwork: Multi-Domain Cross Stitched Network for Deepfake Detection
MD-CSDNetwork is a novel cross-stitched network with two parallel branches carrying the spatial and frequency information, respectively.
Evaluating Empathetic Chatbots in Customer Service Settings
Customer service is a setting that calls for empathy in live human agent responses.
WaveTransform: Crafting Adversarial Examples via Input Decomposition
Experiments are performed using multiple databases and CNN models to establish the effectiveness of the proposed WaveTransform attack and analyze the importance of a particular frequency component.
Attack Agnostic Adversarial Defense via Visual Imperceptible Bound
However, the lack of generalizability of existing defense algorithms and the high variability in the performance of the attack algorithms for different databases raises several questions on the effectiveness of the defense algorithms.
MixNet for Generalized Face Presentation Attack Detection
The major problem with existing work is the generalizability against multiple attacks both in the seen and unseen setting.
Generalized Iris Presentation Attack Detection Algorithm under Cross-Database Settings
Presentation attacks are posing major challenges to most of the biometric modalities.
On the Robustness of Face Recognition Algorithms Against Attacks and Bias
Face recognition algorithms have demonstrated very high recognition performance, suggesting suitability for real world applications.
Unravelling Robustness of Deep Learning based Face Recognition Against Adversarial Attacks
In this paper, we attempt to unravel three aspects related to the robustness of DNNs for face recognition: (i) assessing the impact of deep architectures for face recognition in terms of vulnerabilities to attacks inspired by commonly observed distortions in the real world that are well handled by shallow learning methods along with learning based adversaries; (ii) detecting the singularities by characterizing abnormal filter response behavior in the hidden layers of deep networks; and (iii) making corrections to the processing pipeline to alleviate the problem.
