Adversarial Attacks Assessment of Salient Object Detection via Symbolic Learning

no code implementations • 12 Sep 2023 • Gustavo Olague, Roberto Pineda, Gerardo Ibarra-Vazquez, Matthieu Olague, Axel Martinez, Sambit Bakshi, Jonathan Vargas, Isnardo Reducindo

We test this evolutionary computation methodology against several adversarial attacks and noise perturbations using standard databases and a real-world problem of a shorebird called the Snowy Plover portraying a visual attention task.

object-detection Object Detection +1

Localization of Unmanned Aerial Vehicles in Corridor Environments using Deep Learning

no code implementations • 21 Mar 2019 • Ram Prasad Padhy, Shahzad Ahmad, Sachin Verma, Pankaj Kumar Sa, Sambit Bakshi

When the UAV is at the center of the corridor, a new image is passed through another trained DNN to predict the orientation of the UAV with respect to the CBL of the corridor.

Navigate Pose Estimation

The Unconstrained Ear Recognition Challenge 2019 - ArXiv Version With Appendix

no code implementations • 11 Mar 2019 • Žiga Emeršič, Aruna Kumar S. V., B. S. Harish, Weronika Gutfeter, Jalil Nourmohammadi Khiarak, Andrzej Pacut, Earnest Hansley, Mauricio Pamplona Segundo, Sudeep Sarkar, Hyeonjung Park, Gi Pyo Nam, Ig-Jae Kim, Sagar G. Sangodkar, Ümit Kaçar, Murvet Kirci, Li Yuan, Jishou Yuan, Haonan Zhao, Fei Lu, Junying Mao, Xiaoshuang Zhang, Dogucan Yaman, Fevziye Irem Eyiokur, Kadir Bulut Özler, Hazim Kemal Ekenel, Debbrota Paul Chowdhury, Sambit Bakshi, Pankaj K. Sa, Banshidhar Majhi, Peter Peer, Vitomir Štruc

The goal of the challenge is to assess the performance of existing ear recognition techniques on a challenging large-scale ear dataset and to analyze performance of the technology from various viewpoints, such as generalization abilities to unseen data characteristics, sensitivity to rotations, occlusions and image resolution and performance bias on sub-groups of subjects, selected based on demographic criteria, i. e. gender and ethnicity.

Benchmarking Person Recognition