Shashank Kotyan

According to our database, Shashank Kotyan authored at least 18 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Improving robustness for vision transformer with a simple dynamic scanning augmentation.

Shashank Kotyan, Danilo Vasconcellos Vargas

Neurocomputing, January, 2024

Linking Robustness and Generalization: A k* Distribution Analysis of Concept Clustering in Latent Space for Vision Models.

Shashank Kotyan, Pin-Yu Chen, Danilo Vasconcellos Vargas

CoRR, 2024

EvoSeed: Unveiling the Threat on Deep Neural Networks with Real-World Illusions.

Shashank Kotyan, Poyuan Mao, Danilo Vasconcellos Vargas

CoRR, 2024

2023

Synthetic Shifts to Initial Seed Vector Exposes the Brittle Nature of Latent-Based Diffusion Models.

Poyuan Mao, Shashank Kotyan, Tham Yik Foong, Danilo Vasconcellos Vargas

CoRR, 2023

k* Distribution: Evaluating the Latent Space of Deep Neural Networks using Local Neighborhood Analysis.

Shashank Kotyan, Tatsuya Ueda, Danilo Vasconcellos Vargas

CoRR, 2023

The Challenges of Image Generation Models in Generating Multi-Component Images.

Tham Yik Foong, Shashank Kotyan, Poyuan Mao, Danilo Vasconcellos Vargas

CoRR, 2023

Towards Improving Robustness Against Common Corruptions using Mixture of Class Specific Experts.

Shashank Kotyan, Danilo Vasconcellos Vargas

CoRR, 2023

Towards Improving Robustness Against Common Corruptions in Object Detectors Using Adversarial Contrastive Learning.

Shashank Kotyan, Danilo Vasconcellos Vargas

CoRR, 2023

A reading survey on adversarial machine learning: Adversarial attacks and their understanding.

Shashank Kotyan

CoRR, 2023

2021

Deep Neural Network Loses Attention to Adversarial Images.

Shashank Kotyan, Danilo Vasconcellos Vargas

Proceedings of the Workshop on Artificial Intelligence Safety 2021 co-located with the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI 2021), 2021

2020

Evolving Robust Neural Architectures to Defend from Adversarial Attacks.

Shashank Kotyan, Danilo Vasconcellos Vargas

Proceedings of the Workshop on Artificial Intelligence Safety 2020 co-located with the 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence (IJCAI-PRICAI 2020), 2020

Towards evolving robust neural architectures to defend from adversarial attacks.

Shashank Kotyan, Danilo Vasconcellos Vargas

Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

2019

Analysis and Comparison of Different Fuzzy Inference Systems Used in Decision Making for Secondary Users in Cognitive Radio Network.

Shrivishal Tripathi, Ashish Upadhyay, Shashank Kotyan, Sandeep Yadav

Wirel. Pers. Commun., 2019

Uncovering Why Deep Neural Networks Lack Robustness: Representation Metrics that Link to Adversarial Attacks.

Danilo Vasconcellos Vargas, Shashank Kotyan, Moe Matsuki

CoRR, 2019

Model Agnostic Dual Quality Assessment for Adversarial Machine Learning and an Analysis of Current Neural Networks and Defenses.

Danilo Vasconcellos Vargas, Shashank Kotyan

CoRR, 2019

HAUAR: Home Automation Using Action Recognition.

Shashank Kotyan, Nishant Kumar, Pankaj Kumar Sahu, Venkanna Udutalapally

CoRR, 2019

Drishtikon: An advanced navigational aid system for visually impaired people.

Shashank Kotyan, Nishant Kumar, Pankaj Kumar Sahu, Venkanna Udutalapally

CoRR, 2019

Self Training Autonomous Driving Agent.

Shashank Kotyan, Danilo Vasconcellos Vargas, Venkanna Udutalapally

Proceedings of the 58th Annual Conference of the Society of Instrument and Control Engineers of Japan, 2019