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1
Optimization matters guidelines to improve representation learning with deep networks
Optimization matters guidelines to improve representation learning with deep networks
Material Type:
Conference Paper 		Add to e-Shelf

Optimization matters guidelines to improve representation learning with deep networks

Aline Regina Becher Moacir Antonelli Ponti; Encontro Nacional de Inteligência Artificial e Computacional - ENIAC (18. 2021 Evento Online)

Anais Porto Alegre : SBC, 2021

Porto Alegre SBC 2021

Online access. The library also has physical copies.

2
Unsupervised representation learning using convolutional and stacked auto-encoders a domain and cross-domain feature space analysis
Unsupervised representation learning using convolutional and stacked auto-encoders a domain and cross-domain feature space analysis
Material Type:
Conference Paper 		Add to e-Shelf

Unsupervised representation learning using convolutional and stacked auto-encoders a domain and cross-domain feature space analysis

Gabriel B Cavallari Leonardo Sampaio F Ribeiro; Moacir Antonelli Ponti; Conference on Graphics, Patterns and Images - SIBGRAPI (31. 2018 Foz do Iguaçu)

Proceedings Los Alamitos : IEEE, 2018

Los Alamitos IEEE 2018

Available at ICMC - Inst. Ciên. Mat. Computação    (PROD-2922392 )(GetIt)

3
Combining clustering and active learning for the detection and learning of new image classes
Combining clustering and active learning for the detection and learning of new image classes
Material Type:
Article 		Add to e-Shelf

Combining clustering and active learning for the detection and learning of new image classes

Luiz Fernando Sommaggio Coletta Moacir Antonelli Ponti; Eduardo Raul Hruschka 1972-; Ayan Acharya; Joydeep Ghosh

Neurocomputing Amsterdam : Elsevier v. 358, p. 150-165, Sep. 2019

Amsterdam 2019

Available at ICMC - Inst. Ciên. Mat. Computação    (PROD-2942142 )(GetIt)

4
Semi-supervised siamese network using self-supervision under scarce annotation improves class separability and robustness to attack
Semi-supervised siamese network using self-supervision under scarce annotation improves class separability and robustness to attack
Material Type:
Conference Paper 		Add to e-Shelf

Semi-supervised siamese network using self-supervision under scarce annotation improves class separability and robustness to attack

Gabriel Biscaro Cavallari Moacir Antonelli Ponti; Conference on Graphics, Patterns and Images - SIBGRAPI (34. 2021 Gramado)

Proceedings Los Alamitos : IEEE, 2021

Los Alamitos IEEE 2021

Available at ICMC - Inst. Ciên. Mat. Computação    (PROD-3057136 )(GetIt)

5
Color quantization in transfer learning and noisy scenarios an empirical analysis using convolutional networks
Color quantization in transfer learning and noisy scenarios an empirical analysis using convolutional networks
Material Type:
Conference Paper 		Add to e-Shelf

Color quantization in transfer learning and noisy scenarios an empirical analysis using convolutional networks

Tiago Santana de Nazaré Gabriel B. Paranhos da Costa; Rodrigo Fernandes de Mello; Moacir Antonelli Ponti; Conference on Graphics, Patterns and Images - SIBGRAPI (31. 2018 Foz do Iguaçu)

Proceedings Los Alamitos : IEEE, 2018

Los Alamitos IEEE 2018

Available at ICMC - Inst. Ciên. Mat. Computação    (PROD-2922387 )(GetIt)

6
Features transfer learning for image and video recognition tasks
Features transfer learning for image and video recognition tasks
Material Type:
Conference Paper 		Add to e-Shelf

Features transfer learning for image and video recognition tasks

Fernando Pereira dos Santos Moacir Antonelli Ponti; Conference on Graphics, Patterns and Images - SIBGRAPI (33. 2020 Recife/Porto de Galinhas); Workshop de Teses e Dissertações - WTD (2020 Recife/Porto de Galinhas)

Anais estendidos Porto Alegre : SBC, 2020

Porto Alegre SBC 2020

Online access. The library also has physical copies.

7
Training deep networks from zero to hero avoiding pitfalls and going beyond
Training deep networks from zero to hero avoiding pitfalls and going beyond
Material Type:
Conference Paper 		Add to e-Shelf

Training deep networks from zero to hero avoiding pitfalls and going beyond

Moacir Antonelli Ponti Fernando Pereira dos Santos; Leo Sampaio Ferraz Ribeiro; Gabriel Biscaro Cavallari; Conference on Graphics, Patterns and Images - SIBGRAPI (34. 2021 Gramado)

Proceedings Los Alamitos : IEEE, 2021

Los Alamitos IEEE 2021

Available at ICMC - Inst. Ciên. Mat. Computação    (PROD-3057145 )(GetIt)

8
Data augmentation guidelines for cross-dataset transfer learning and pseudo labeling
Data augmentation guidelines for cross-dataset transfer learning and pseudo labeling
Material Type:
Conference Paper 		Add to e-Shelf

Data augmentation guidelines for cross-dataset transfer learning and pseudo labeling

Fernando Pereira dos Santos Gabriela Salvador Thumé; Moacir Antonelli Ponti; Conference on Graphics, Patterns and Images - SIBGRAPI (34. 2021 Gramado)

Proceedings Los Alamitos : IEEE, 2021

Los Alamitos IEEE 2021

Available at ICMC - Inst. Ciên. Mat. Computação    (PROD-3057130 )(GetIt)

9
Scene Designer a unified model for scene search and synthesis from sketch
Scene Designer a unified model for scene search and synthesis from sketch
Material Type:
Conference Paper 		Add to e-Shelf

Scene Designer a unified model for scene search and synthesis from sketch

Leo Sampaio Ferraz Ribeiro Tu Bui; John Collomosse; Moacir Antonelli Ponti; IEEE/CVF International Conference on Computer Vision Workshops - ICCVW (2021 Virtual Event)

Proceedings Los Alamitos : IEEE, 2021

Los Alamitos IEEE 2021

Available at ICMC - Inst. Ciên. Mat. Computação    (PROD-3057717 )(GetIt)

10
Deep convolutional neural networks and noisy images
Deep convolutional neural networks and noisy images
Material Type:
Conference Paper 		Add to e-Shelf

Deep convolutional neural networks and noisy images

Tiago Santana de Nazaré Gabriel B. Paranhos da Costa; Welinton A Contato; Moacir Antonelli Ponti; Iberoamerican Congress on Pattern Recognition - CIARP : Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications (22. 2017 Valparaíso)

Lecture Notes in Computer Science Cham : Springer v. 10657, p. 416-424, 2018

Cham Springer 2018

Available at ICMC - Inst. Ciên. Mat. Computação    (PROD-2877039 )(GetIt)

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by this author/creator:

  1. Ponti, M
  2. Ribeiro, L
  3. Conference on Graphics, P
  4. Santos, F
  5. Bui, T

on this subject:

  1. Aprendizado Computacional
  2. Redes Neurais
  3. Reconhecimento De Imagem
  4. Processamento De Imagens
  5. Visão Computacional

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