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SCD - Sitemas de Controle Dinâmicos: Função de Transferência
SCD - Sitemas de Controle Dinâmicos: Função de Transferência
Trabalho apresentado na Disciplina: Modelagem de Modelos Matemáticos no CEFET-MG Unidade Timóteo/MG
Egmon Pereira e Igor Otoni
Níckolas Alves' Academic CV
Níckolas Alves' Academic CV
Níckolas Alves' Academic CV Created with the AltaCV template
Níckolas Alves
Sidney Hann's Résumé
Sidney Hann's Résumé
Sidney Hann's résumé. Created using Ganesh Mohan's résumé template.
Sidney Hann
Abdallah Meddah's CV
Abdallah Meddah's CV
Abdallah Meddah's CV. Created with the AltaCV template.
Abdallah Meddah
Aadhithya Dinesh's Resume
Aadhithya Dinesh's Resume
Aadhithya Dinesh's Resume
Aadhithya Dinesh
Ali Özen's Resume
Ali Özen's Resume
Ali Özen's Resume. Created using the Deedy CV template.
Ali Özen
Conservative Wasserstein Training for Pose Estimation
Conservative Wasserstein Training for Pose Estimation
Paper presented at ICCV 2019. This paper targets the task with discrete and periodic class labels (e.g., pose/orientation estimation) in the context of deep learning. The commonly used cross-entropy or regression loss is not well matched to this problem as they ignore the periodic nature of the labels and the class similarity, or assume labels are continuous value. We propose to incorporate inter-class correlations in a Wasserstein training framework by pre-defining (i.e., using arc length of a circle) or adaptively learning the ground metric. We extend the ground metric as a linear, convex or concave increasing function w.r.t. arc length from an optimization perspective. We also propose to construct the conservative target labels which model the inlier and outlier noises using a wrapped unimodal-uniform mixture distribution. Unlike the one-hot setting, the conservative label makes the computation of Wasserstein distance more challenging. We systematically conclude the practical closed-form solution of Wasserstein distance for pose data with either one-hot or conservative target label. We evaluate our method on head, body, vehicle and 3D object pose benchmarks with exhaustive ablation studies. The Wasserstein loss obtaining superior performance over the current methods, especially using convex mapping function for ground metric, conservative label, and closed-form solution.
Xiaofeng Liu, Yang Zou, Tong Che, Peng Ding, Ping Jia, Jane You, B.V.K. Vijaya Kumar
Group Isomorphism
Group Isomorphism
Group Isomorphisms
Srishti Patel
The Logarithmic Method of Ranking Stocks
The Logarithmic Method of Ranking Stocks
A ranking system for tech stocks and bank stocks of S&P 500 companies
Albert Liang