Effective, Efficient, and Scalable Unsupervised Distance Learning in Image Retrieval Tasks. - Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette; Ricardo da Silva Torres; Edson Borin; Jurandy Almeida (ICMR, 2015)

Unsupervised Similarity Learning through Cartesian Product of Ranking References for Image Retrieval Tasks. - Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (SIBGRAPI, 2016)

Selection and Combination of Unsupervised Learning Methods for Image Retrieval. - Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (CBMI, 2017)

A Rank Aggregation Framework for Video Interestingness Prediction. - Jurandy Almeida; Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (ICIAP (1), 2017)

An Unsupervised Distance Learning Framework for Multimedia Retrieval. - Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (ICMR, 2017)

Manifold Correlation Graph for Semi-Supervised Learning. - Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette; Fabricio Aparecido Breve; Ivan Rizzo Guilherme (IJCNN, 2018)

Unsupervised similarity learning through Cartesian product of ranking references. - Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette; Jurandy Almeida (Pattern Recognit. Lett., 2018)

Unsupervised Similarity Learning through Rank Correlation and kNN Sets. - Lucas Pascotti Valem; Carlos Renan De Oliveira; Daniel Carlos Guimarães Pedronette; Jurandy Almeida (ACM Trans. Multim. Comput. Commun. Appl., 2018)

Unsupervised Effectiveness Estimation Through Intersection of Ranking References. - João Gabriel Camacho Presotto; Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (CAIP (2), 2019)

An Unsupervised Genetic Algorithm Framework for Rank Selection and Fusion on Image Retrieval. - Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (ICMR, 2019)

Multimedia Retrieval Through Unsupervised Hypergraph-Based Manifold Ranking. - Daniel Carlos Guimarães Pedronette; Lucas Pascotti Valem; Jurandy Almeida; Ricardo da Silva Torres (IEEE Trans. Image Process., 2019)

Weakly Supervised Learning through Rank-based Contextual Measures. - João Gabriel Camacho Presotto; Lucas Pascotti Valem; Nikolas Gomes de Sá; Daniel Carlos Guimarães Pedronette; João Paulo Papa (ICPR, 2020)

RaDE: A Rank-based Graph Embedding Approach. - Filipe Alves de Fernando; Daniel Carlos Guimarães Pedronette; Gustavo José de Sousa; Lucas Pascotti Valem; Ivan Rizzo Guilherme (VISIGRAPP (5: VISAPP), 2020)

Manifold Learning-based Clustering Approach Applied to Anomaly Detection in Surveillance Videos. - Leonardo Tadeu Lopes; Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette; Ivan Rizzo Guilherme; João Paulo Papa; Marcos Cleison Silva Santana; Danilo Colombo (VISIGRAPP (5: VISAPP), 2020)

A unified model for accelerating unsupervised iterative re-ranking algorithms. - Flávia Pisani; Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette; Ricardo da Silva Torres; Edson Borin; Maurício Breternitz Jr. (Concurr. Comput. Pract. Exp., 2020)

Unsupervised selective rank fusion for image retrieval tasks. - Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (Neurocomputing, 2020)

Graph-based selective rank fusion for unsupervised image retrieval. - Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (Pattern Recognit. Lett., 2020)

A Denoising Convolutional Neural Network for Self-Supervised Rank Effectiveness Estimation on Image Retrieval. - Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (ICMR, 2021)

Representation Learning for Image Retrieval through 3D CNN and Manifold Ranking. - Lucas Barbosa de Almeida; Vanessa Helena Pereira-Ferrero; Lucas Pascotti Valem; Jurandy Almeida; Daniel Carlos Guimarães Pedronette (SIBGRAPI, 2021)

A Multi-level Rank Correlation Measure for Image Retrieval. - Nikolas Gomes de Sá; Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (VISIGRAPP (5: VISAPP), 2021)

Efficient Rank-Based Diffusion Process with Assured Convergence. - Daniel Carlos Guimarães Pedronette; Lucas Pascotti Valem; Longin Jan Latecki (J. Imaging, 2021)

A BFS-Tree of ranking references for unsupervised manifold learning. - Daniel Carlos Guimarães Pedronette; Lucas Pascotti Valem; Ricardo da Silva Torres (Pattern Recognit., 2021)

Graph Convolutional Networks and Manifold Ranking for Multimodal Video Retrieval. - Lucas Barbosa de Almeida; Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (ICIP, 2022)

A Novel Rank Correlation Measure for Manifold Learning on Image Retrieval and Person Re-ID. - Lucas Pascotti Valem; Vinicius Atsushi Sato Kawai; Vanessa Helena Pereira-Ferrero; Daniel Carlos Guimarães Pedronette (ICIP, 2022)

RaDE+: A semantic rank-based graph embedding algorithm. - Filipe Alves de Fernando; Daniel Carlos Guimarães Pedronette; Gustavo José de Sousa; Lucas Pascotti Valem; Ivan Rizzo Guilherme (Int. J. Inf. Manag. Data Insights, 2022)

Person Re-ID through unsupervised hypergraph rank selection and fusion. - Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (Image Vis. Comput., 2022)

Weakly supervised learning based on hypergraph manifold ranking. - João Gabriel Camacho Presotto; Samuel Felipe dos Santos; Lucas Pascotti Valem; Fábio Augusto Faria; João Paulo Papa; Jurandy Almeida; Daniel Carlos Guimarães Pedronette (J. Vis. Commun. Image Represent., 2022)

Self-Supervised Regression for Query Performance Prediction on Image Retrieval. - Lucas Pascotti Valem; Vanessa Helena Pereira-Ferrero; Daniel Carlos Guimarães Pedronette (AIKE, 2023)

pyUDLF: A Python Framework for Unsupervised Distance Learning Tasks. - Gustavo Leticio; Lucas Pascotti Valem; Leonardo Tadeu Lopes; Daniel Carlos Guimarães Pedronette (ACM Multimedia, 2023)

Gait Recognition Based on Deep Learning: A Survey. - Claudio Filipi Gonçalves dos Santos; Diego de Souza Oliveira; Leandro A. Passos; Rafael Gonçalves Pires; Daniel Felipe Silva Santos; Lucas Pascotti Valem; Thierry Pinheiro Moreira; Marcos Cleison S. Santana; Mateus Roder; João Paulo Papa; Danilo Colombo (ACM Comput. Surv., 2023)

Feature augmentation based on manifold ranking and LSTM for image classification. - Vanessa Helena Pereira-Ferrero; Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (Expert Syst. Appl., 2023)

Rank Flow Embedding for Unsupervised and Semi-Supervised Manifold Learning. - Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette; Longin Jan Latecki (IEEE Trans. Image Process., 2023)

Graph Convolutional Networks based on manifold learning for semi-supervised image classification. - Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette; Longin Jan Latecki (Comput. Vis. Image Underst., 2023)

Unsupervised Effectiveness Estimation Measure Based on Rank Correlation for Image Retrieval. - Thiago César Castilho Almeida; Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (ISVC (2), 2024)

Contrastive Loss Based on Contextual Similarity for Image Classification. - Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette; Mohand Saïd Allili (ISVC (1), 2024)

Feature Fusion for Graph Convolutional Networks in Semi-Supervised Image Classification. - Marina Chagas Bulach Gapski; Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (SIBGRAPI, 2024)

Neighbor Embedding Projection and Rank-Based Manifold Learning for Image Retrieval. - Vinicius Atsushi Sato Kawai; Gustavo Rosseto Leticio; Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (SIBGRAPI, 2024)

Self-Supervised Image Re-Ranking based on Hypergraphs and Graph Convolutional Networks. - Leonardo Tadeu Lopes; Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (SIBGRAPI, 2024)

Unsupervised affinity learning based on manifold analysis for image retrieval: A survey. - Vanessa Helena Pereira-Ferrero; Ted G. Lewis; Lucas Pascotti Valem; L. G. P. Ferrero; Daniel C. G. Pedronette; Longin Jan Latecki (Comput. Sci. Rev., 2024)

Weakly supervised classification through manifold learning and rank-based contextual measures. - João Gabriel Camacho Presotto; Lucas Pascotti Valem; Nikolas Gomes de Sá; Daniel Carlos Guimarães Pedronette; João Paulo Papa (Neurocomputing, 2024)

Manifold information through neighbor embedding projection for image retrieval. - Gustavo Rosseto Leticio; Vinicius Atsushi Sato Kawai; Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette; Ricardo da Silva Torres (Pattern Recognit. Lett., 2024)

Rank-based Hashing for Effective and Efficient Nearest Neighbor Search for Image Retrieval. - Vinicius Atsushi Sato Kawai; Lucas Pascotti Valem; Alexandro Baldassin; Edson Borin; Daniel Carlos Guimarães Pedronette; Longin Jan Latecki (ACM Trans. Multim. Comput. Commun. Appl., 2024)

Feature Fusion and Augmentation Based on Manifold Ranking for Image Classification. - Vanessa Helena Pereira-Ferrero; Lucas Pascotti Valem; Gustavo Rosseto Leticio; Daniel Carlos Guimarães Pedronette (Int. J. Semantic Comput., 2024)

Neighbor Embedding Projection and Graph Convolutional Networks for Image Classification. - Gustavo Rosseto Leticio; Vinicius Atsushi Sato Kawai; Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette (VISIGRAPP (2): VISAPP, 2025)

Graph Convolutional Networks and Particle Competition and Cooperation for Semi-Supervised Learning. - Gustavo Rosseto Leticio; Matheus Henrique Jacob dos Santos; Lucas Pascotti Valem; Vinicius Atsushi Sato Kawai; Fabricio Aparecido Breve; Daniel Carlos Guimarães Pedronette (VISIGRAPP (2): VISAPP, 2025)

Transduction to induction: Unsupervised representation learning based on rank information. - Deryk Willyan Biotto; Lucas Pascotti Valem; Daniel Carlos Guimarães Pedronette; Denis Henrique Pinheiro Salvadeo (Neurocomputing, 2025)