Search Results for author: Mauricio Pamplona Segundo

Found 10 papers, 7 papers with code

Reducing Training Demands for 3D Gait Recognition with Deep Koopman Operator Constraints

no code implementations14 Aug 2023 Cole Hill, Mauricio Pamplona Segundo, Sudeep Sarkar

Deep learning research has made many biometric recognition solution viable, but it requires vast training data to achieve real-world generalization.

Gait Recognition

Shape-Graph Matching Network (SGM-net): Registration for Statistical Shape Analysis

no code implementations14 Aug 2023 Shenyuan Liang, Mauricio Pamplona Segundo, Sathyanarayanan N. Aakur, Sudeep Sarkar, Anuj Srivastava

This, in turn, requires optimization over the permutation group, made challenging by differences in nodes (in terms of numbers, locations) and edges (in terms of shapes, placements, and sizes) across objects.

Graph Matching

Fingerprint Pore Detection: A Survey

1 code implementation27 Nov 2022 Azim Ibragimov, Mauricio Pamplona Segundo

We also present a baseline method inspired on the state-of-the-art that implements a customizable Fully Convolutional Network, whose hyperparameters were tuned to achieve optimal pore detection rates.

On deceiving malware classification with section injection

1 code implementation12 Aug 2022 Adeilson Antonio da Silva, Mauricio Pamplona Segundo

Our results show that a mere increase of 7% in the malware size causes an accuracy drop between 25% and 40% for malware family classification.

Classification Malware Classification

Measuring economic activity from space: a case study using flying airplanes and COVID-19

1 code implementation21 Apr 2021 Mauricio Pamplona Segundo, Allan Pinto, Rodrigo Minetto, Ricardo da Silva Torres, Sudeep Sarkar

This work introduces a novel solution to measure economic activity through remote sensing for a wide range of spatial areas.

Level Three Synthetic Fingerprint Generation

2 code implementations5 Feb 2020 André Brasil Vieira Wyzykowski, Mauricio Pamplona Segundo, Rubisley de Paula Lemes

Given that we also favorably compare our results with the most advanced works in the literature, our experimentation suggests that our approach is the new state-of-the-art.

The Unconstrained Ear Recognition Challenge 2019 - ArXiv Version With Appendix

no code implementations11 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

Hydra: an Ensemble of Convolutional Neural Networks for Geospatial Land Classification

1 code implementation10 Feb 2018 Rodrigo Minetto, Mauricio Pamplona Segundo, Sudeep Sarkar

With this framework, we were able to reduce the training time while maintaining the classification performance of the ensemble.

General Classification

Employing Fusion of Learned and Handcrafted Features for Unconstrained Ear Recognition

1 code implementation20 Oct 2017 Earnest E. Hansley, Mauricio Pamplona Segundo, Sudeep Sarkar

We used the results generated to perform a geometric image normalization that boosted the performance of all evaluated descriptors.

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