Document segmentation using textural features summarization and feedforward neural network. - Oyebade K. Oyedotun; Adnan Khashman (Appl. Intell., 2016)

STARR - Decision SupporT and self-mAnagement system for stRoke survivoRs Vision based Rehabilitation System. - Abd El Rahman Shabayek; Renato Baptista; Konstantinos Papadopoulos 002; Girum G. Demisse; Oyebade K. Oyedotun; Michel Antunes; Djamila Aouada; Björn E. Ottersten; Margarita Anastassova; Mehdi Boukallel; Sabrina A. Panëels; Gary Randall; et al. (EPS, 2017)

Facial Expression Recognition via Joint Deep Learning of RGB-Depth Map Latent Representations. - Oyebade K. Oyedotun; Girum G. Demisse; Abd El Rahman Shabayek; Djamila Aouada; Björn E. Ottersten (ICCV Workshops, 2017)

Training Very Deep Networks via Residual Learning with Stochastic Input Shortcut Connections. - Oyebade K. Oyedotun; Abd El Rahman Shabayek; Djamila Aouada; Björn E. Ottersten (ICONIP (2), 2017)

Iris nevus diagnosis: convolutional neural network and deep belief network. - Oyebade K. Oyedotun; Adnan Khashman (Turkish J. Electr. Eng. Comput. Sci., 2017)

A simple and practical review of over-fitting in neural network learning. - Oyebade K. Oyedotun; Ebenezer O. Olaniyi; Adnan Khashman (Int. J. Appl. Pattern Recognit., 2017)

Deep learning in vision-based static hand gesture recognition. - Oyebade K. Oyedotun; Adnan Khashman (Neural Comput. Appl., 2017)

Highway Network Block With Gates Constraints for Training Very Deep Networks. - Oyebade K. Oyedotun; Abd El Rahman Shabayek; Djamila Aouada; Björn E. Ottersten (CVPR Workshops, 2018)

Improving the Capacity of Very Deep Networks with Maxout Units. - Oyebade K. Oyedotun; Abd El Rahman Shabayek; Djamila Aouada; Björn E. Ottersten (ICASSP, 2018)

Prototype-Incorporated Emotional Neural Network. - Oyebade K. Oyedotun; Adnan Khashman (IEEE Trans. Neural Networks Learn. Syst., 2018)

Learning to Fuse Latent Representations for Multimodal Data. - Oyebade K. Oyedotun; Djamila Aouada; Björn E. Ottersten (ICASSP, 2019)

In-line grading system for mango fruits using GLCM feature extraction and soft-computing techniques. - Ebenezer O. Olaniyi; Oyebade K. Oyedotun; Clement A. Ogunlade; Adnan Khashman (Int. J. Appl. Pattern Recognit., 2019)

DeepVI: A Novel Framework for Learning Deep View-Invariant Human Action Representations using a Single RGB Camera. - Konstantinos Papadopoulos 002; Enjie Ghorbel; Oyebade K. Oyedotun; Djamila Aouada; Björn E. Ottersten (FG, 2020)

Going Deeper With Neural Networks Without Skip Connections. - Oyebade K. Oyedotun; Abd El Rahman Shabayek; Djamila Aouada; Björn E. Ottersten (ICIP, 2020)

Why Do Deep Neural Networks with Skip Connections and Concatenated Hidden Representations Work? - Oyebade K. Oyedotun; Djamila Aouada (ICONIP (3), 2020)

Revisiting the Training of Very Deep Neural Networks without Skip Connections. - Oyebade K. Oyedotun; Abd El Rahman Shabayek; Djamila Aouada; Björn E. Ottersten (ICPR, 2020)

Structured Compression of Deep Neural Networks with Debiased Elastic Group LASSO. - Oyebade K. Oyedotun; Djamila Aouada; Björn E. Ottersten (WACV, 2020)

Improved Highway Network Block for Training Very Deep Neural Networks. - Oyebade K. Oyedotun; Abd El Rahman Shabayek; Djamila Aouada; Björn E. Ottersten (IEEE Access, 2020)

Analyzing and Improving Very Deep Neural Networks: From Optimization, Generalization to Compression. - Oyebade Kayode Oyedotun (2020)

Deep network compression with teacher latent subspace learning and LASSO. - Oyebade K. Oyedotun; Abd El Rahman Shabayek; Djamila Aouada; Björn E. Ottersten (Appl. Intell., 2021)

SPARK: SPAcecraft Recognition leveraging Knowledge of Space Environment. - Mohamed Adel Musallam; Kassem Al Ismaeil; Oyebade K. Oyedotun; Marcos Damian Perez; Michel Poucet; Djamila Aouada (CoRR, 2021)

Training very deep neural networks: Rethinking the role of skip connections. - Oyebade K. Oyedotun; Kassem Al Ismaeil; Djamila Aouada (Neurocomputing, 2021)

A Closer Look at Autoencoders for Unsupervised Anomaly Detection. - Oyebade K. Oyedotun; Djamila Aouada (ICASSP, 2022)

Multi Label Image Classification using Adaptive Graph Convolutional Networks (ML-AGCN). - Inder Pal Singh; Enjie Ghorbel; Oyebade K. Oyedotun; Djamila Aouada (ICIP, 2022)

A new perspective for understanding generalization gap of deep neural networks trained with large batch sizes. - Oyebade K. Oyedotun; Konstantinos Papadopoulos 002; Djamila Aouada (Appl. Intell., 2023)

Why Is Everyone Training Very Deep Neural Network With Skip Connections? - Oyebade K. Oyedotun; Kassem Al Ismaeil; Djamila Aouada (IEEE Trans. Neural Networks Learn. Syst., 2023)

Multi-label image classification using adaptive graph convolutional networks: From a single domain to multiple domains. - Inder Pal Singh; Enjie Ghorbel; Oyebade Kayode Oyedotun; Djamila Aouada (Comput. Vis. Image Underst., 2024)