Statistical modelling of outliers for fast visual search. - Skjalg Lepsøy; Gianluca Francini; Giovanni Cordara; Pedro P. B. de Gusmao (ICME, 2011)

Loop detection in robotic navigation using MPEG CDVS. - Pedro P. B. de Gusmao; Stefano Rosa; Enrico Magli; Skjalg Lepsøy; Gianluca Francini (MMSP, 2015)

Gabor filter based image representation for object classification. - Syed Tahir Hussain Rizvi; Gianpiero Cabodi; Pedro P. B. de Gusmao; Gianluca Francini (CoDIT, 2016)

Fast Training of Convolutional Neural Networks via Kernel Rescaling. - Pedro Porto Buarque de Gusmão; Gianluca Francini; Skjalg Lepsøy; Enrico Magli (CoRR, 2016)

Feature extraction using MPEG-CDVS and Deep Learning with application to robotic navigation and image classification. - Pedro Porto Buarque de Gusmão (2017)

Map-aided Navigation for Emergency Searches. - Johan Wahlström; Pedro Porto Buarque de Gusmão; Andrew Markham; Niki Trigoni (DCOSS, 2019)

Distilling Knowledge From a Deep Pose Regressor Network. - Muhamad Risqi Utama Saputra; Pedro Porto Buarque de Gusmão; Yasin Almalioglu; Andrew Markham; Niki Trigoni (ICCV, 2019)

GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks. - Yasin Almalioglu; Muhamad Risqi Utama Saputra; Pedro Porto Buarque de Gusmão; Andrew Markham; Niki Trigoni (ICRA, 2019)

Learning Monocular Visual Odometry through Geometry-Aware Curriculum Learning. - Muhamad Risqi Utama Saputra; Pedro P. B. de Gusmao; Sen Wang 002; Andrew Markham; Niki Trigoni (ICRA, 2019)

DeepPCO: End-to-End Point Cloud Odometry through Deep Parallel Neural Network. - Wei Wang 226; Muhamad Risqi Utama Saputra; Peijun Zhao; Pedro P. B. de Gusmao; Bo Yang 027; Changhao Chen; Andrew Markham; Niki Trigoni (IROS, 2019)

SelfVIO: Self-Supervised Deep Monocular Visual-Inertial Odometry and Depth Estimation. - Yasin Almalioglu; Mehmet Turan; Alp Eren Sari; Muhamad Risqi Utama Saputra; Pedro Porto Buarque de Gusmão; Andrew Markham; Niki Trigoni (CoRR, 2019)

milliEgo: single-chip mmWave radar aided egomotion estimation via deep sensor fusion. - Chris Xiaoxuan Lu; Muhamad Risqi Utama Saputra; Peijun Zhao; Yasin Almalioglu; Pedro P. B. de Gusmao; Changhao Chen; Ke Sun 012; Niki Trigoni; Andrew Markham (SenSys, 2020)

milliEgo: mmWave Aided Egomotion Estimation with Deep Sensor Fusion. - Chris Xiaoxuan Lu; Muhamad Risqi Utama Saputra; Peijun Zhao; Yasin Almalioglu; Pedro P. B. de Gusmao; Changhao Chen; Ke Sun 012; Niki Trigoni; Andrew Markham (CoRR, 2020)

DeepTIO: A Deep Thermal-Inertial Odometry With Visual Hallucination. - Muhamad Risqi Utama Saputra; Niki Trigoni; Pedro P. B. de Gusmao; Chris Xiaoxuan Lu; Yasin Almalioglu; Stefano Rosa; Changhao Chen; Johan Wahlström; Wei Wang 226; Andrew Markham (IEEE Robotics Autom. Lett., 2020)

Secure aggregation for federated learning in flower. - Kwing Hei Li; Pedro Porto Buarque de Gusmão; Daniel J. Beutel; Nicholas D. Lane (DistributedML@CoNEXT, 2021)

RadarLoc: Learning to Relocalize in FMCW Radar. - Wei Wang 226; Pedro Porto Buarque de Gusmão; Bo Yang 027; Andrew Markham; Niki Trigoni (ICRA, 2021)

A first look into the carbon footprint of federated learning. - Xinchi Qiu; Titouan Parcollet; Javier Fernández-Marqués; Pedro Porto Buarque de Gusmão; Daniel J. Beutel; Taner Topal; Akhil Mathur; Nicholas D. Lane (CoRR, 2021)

On-device Federated Learning with Flower. - Akhil Mathur; Daniel J. Beutel; Pedro Porto Buarque de Gusmão; Javier Fernández-Marqués; Taner Topal; Xinchi Qiu; Titouan Parcollet; Yan Gao 016; Nicholas D. Lane (CoRR, 2021)

End-to-End Speech Recognition from Federated Acoustic Models. - Yan Gao 016; Titouan Parcollet; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Daniel J. Beutel; Nicholas D. Lane (CoRR, 2021)

Federated Self-supervised Learning for Video Understanding. - Yasar Abbas Ur Rehman; Yan Gao 016; Jiajun Shen; Pedro Porto Buarque de Gusmão; Nicholas D. Lane (ECCV (31), 2022)

Protea: client profiling within federated systems using flower. - Wanru Zhao; Xinchi Qiu; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Nicholas D. Lane (FedEdge@MobiCom, 2022)

End-to-End Speech Recognition from Federated Acoustic Models. - Yan Gao 016; Titouan Parcollet; Salah Zaiem; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Daniel J. Beutel; Nicholas D. Lane (ICASSP, 2022)

ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity. - Xinchi Qiu; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Yan Gao 016; Titouan Parcollet; Nicholas Donald Lane (ICLR, 2022)

Match to Win: Analysing Sequences Lengths for Efficient Self-Supervised Learning in Speech and Audio. - Yan Gao 016; Javier Fernández-Marqués; Titouan Parcollet; Pedro P. B. de Gusmao; Nicholas D. Lane (SLT, 2022)

SelfVIO: Self-supervised deep monocular Visual-Inertial Odometry and depth estimation. - Yasin Almalioglu; Mehmet Turan; Muhamad Risqi Utama Saputra; Pedro Porto Buarque de Gusmão; Andrew Markham; Niki Trigoni (Neural Networks, 2022)

Graph-Based Thermal-Inertial SLAM With Probabilistic Neural Networks. - Muhamad Risqi Utama Saputra; Chris Xiaoxuan Lu; Pedro Porto Buarque de Gusmão; Bing Wang 013; Andrew Markham; Niki Trigoni (IEEE Trans. Robotics, 2022)

Can Fair Federated Learning Reduce the need for Personalisation? - Alex Iacob; Pedro Porto Buarque de Gusmão; Nicholas D. Lane (EuroMLSys@EuroSys, 2023)

L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning. - Yasar Abbas Ur Rehman; Yan Gao 016; Pedro Porto Buarque de Gusmão; Mina Alibeigi; Jiajun Shen; Nicholas D. Lane (ICCV, 2023)

FedVal: Different good or different bad in federated learning. - Viktor Valadi; Xinchi Qiu; Pedro Porto Buarque de Gusmão; Nicholas D. Lane; Mina Alibeigi (USENIX Security Symposium, 2023)

Decentralized Training of 3D Lane Detection with Automatic Labeling Using HD Maps. - Yadong Mao; Zhuqi Xiao; Che-Tsung Lin; Pedro Porto Buarque de Gusmão; Nicholas D. Lane; Christopher Zach; Mina Alibeigi (VTC2023-Spring, 2023)

Efficient Vertical Federated Learning with Secure Aggregation. - Xinchi Qiu; Heng Pan; Wanru Zhao; Chenyang Ma; Pedro Porto Buarque de Gusmão; Nicholas D. Lane (CoRR, 2023)

Privacy in Multimodal Federated Human Activity Recognition. - Alex Iacob; Pedro Porto Buarque de Gusmão; Nicholas D. Lane; Armand K. Koupai; Mohammud Junaid Bocus; Raúl Santos-Rodríguez; Robert J. Piechocki; Ryan McConville (CoRR, 2023)

vFedSec: Efficient Secure Aggregation for Vertical Federated Learning via Secure Layer. - Xinchi Qiu; Heng Pan; Wanru Zhao; Chenyang Ma; Pedro P. B. de Gusmao; Nicholas D. Lane (CoRR, 2023)

High-throughput Simulation of Federated Learning via Resource-Aware Client Placement. - Lorenzo Sani; Pedro Porto Buarque de Gusmão; Alex Iacob; Wanru Zhao; Xinchi Qiu; Yan Gao 016; Javier Fernández-Marqués; Nicholas Donald Lane (CoRR, 2023)

A First Look into the Carbon Footprint of Federated Learning. - Xinchi Qiu; Titouan Parcollet; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Yan Gao 016; Daniel J. Beutel; Taner Topal; Akhil Mathur; Nicholas D. Lane (J. Mach. Learn. Res., 2023)

FedRepOpt: Gradient Re-parametrized Optimizers in Federated Learning. - Kin Wai Lau; Yasar Abbas Ur Rehman; Pedro Porto Buarque de Gusmão; Lai-Man Po; Lan Ma; Yuyang Xie (ACCV (8), 2024)

FedAnchor: Enhancing Federated Semi-Supervised Learning with Label Contrastive Loss for Unlabeled Clients. - Xinchi Qiu; Yan Gao 016; Lorenzo Sani; Heng Pan; Wanru Zhao; Pedro P. B. de Gusmao; Mina Alibeigi; Alex Iacob; Nicholas D. Lane (CoRR, 2024)

Federated Learning for Traffic Flow Prediction with Synthetic Data Augmentation. - Fermin Orozco; Pedro Porto Buarque de Gusmão; Hongkai Wen 001; Johan Wahlström; Man Luo 001 (CoRR, 2024)

Improving Semi-Supervised Federated Learning with Limited Labeled Data via Adaptive Batchsize and Pseudo Labeling. - Byoungjun Park; Pedro Porto Buarque de Gusmão; Minhoe Kim (CCNC, 2025)