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researcher

Rafael Rosales

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author1
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.LG1
  • math.DS1
ORCID 0000-0002-7518-2975
same name
  • Rafael Rosales — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedPiecewise contractions defined by iterated function systems

3 citations · 5 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2023

BEA: Revisiting anchor-based object detection DNN using Budding Ensemble Architecture

Syed Sha Qutub, Neslihan Kose, Rafael Rosales +6

This paper introduces the Budding Ensemble Architecture (BEA), a novel reduced ensemble architecture for anchor-based object detection models. Object detection models are crucial i…

cs.LG2023★ 1 cited

Exploring Resiliency to Natural Image Corruptions in Deep Learning using Design Diversity

Rafael Rosales, Pablo Munoz, Michael Paulitsch

In this paper, we investigate the relationship between diversity metrics, accuracy, and resiliency to natural image corruptions of Deep Learning (DL) image classifier ensembles. We…

cs.CV2023★ 1 cited

Evaluation of Confidence-based Ensembling in Deep Learning Image Classification

Rafael Rosales, Peter Popov, Michael Paulitsch

Ensembling is a successful technique to improve the performance of machine learning (ML) models. Conf-Ensemble is an adaptation to Boosting to create ensembles based on model confi…

math.DS2014★ 3 cited

Piecewise contractions defined by iterated function systems

Arnaldo Nogueira, Benito Pires, Rafael A. Rosales

Let ϕ1​,…,ϕn​:[0,1]→(0,1) be Lipschitz contractions. Let I=[0,1), x0​=0 and xn​=1. We prove that for Lebesgue almost every (x1​,...,xn−1​) satisfying $0<x_1<\cd…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.