Buscar
Mostrando ítems 1-5 de 5
Walking Recognition in Mobile Devices
(MDPI AG, 2020-02-21)
[Abstract] Presently, smartphones are used more and more for purposes that have nothing to do with phone calls or simple data transfers. One example is the recognition of human activity, which is relevant information for ...
Concept Drift Detection and Adaptation for Federated and Continual Learning
(Springer, 2021)
[Abstract] Smart devices, such as smartphones, wearables, robots, and others, can collect vast amounts of data from their environment. This data is suitable for training machine learning models, which can significantly ...
Towards a Self-Sufficient Face Verification System
(Elsevier, 2021)
[Abstract] The absence of a previous collaborative manual enrolment represents a significant handicap towards designing a face verification system for face re-identification purposes. In this scenario, the system must learn ...
Incremental Learning from Low-labelled Stream Data in Open-Set Video Face Recognition
(Elsevier, 2022)
[Abstract] Deep Learning approaches have brought solutions, with impressive performance, to general classification problems where wealthy of annotated data are provided for training. In contrast, less progress has been ...
Non-IID data and Continual Learning processes in Federated Learning: A long road ahead
(Elsevier, 2022)
[Abstract] Federated Learning is a novel framework that allows multiple devices or institutions to train a machine learning model collaboratively while preserving their data private. This decentralized approach is prone ...