Zobrazeno 1 - 10
of 77
pro vyhledávání: '"Faria, Diego R."'
In state-of-the-art deep learning for object recognition, SoftMax and Sigmoid functions are most commonly employed as the predictor outputs. Such layers often produce overconfident predictions rather than proper probabilistic scores, which can thus h
Externí odkaz:
http://arxiv.org/abs/2202.07825
Contemporary Artificial Intelligence technologies allow for the employment of Computer Vision to discern good crops from bad, providing a step in the pipeline of selecting healthy fruit from undesirable fruit, such as those which are mouldy or gangre
Externí odkaz:
http://arxiv.org/abs/2104.05647
Autor:
Bachiller, Pilar, Rodriguez-Criado, Daniel, Jorvekar, Ronit R., Bustos, Pablo, Faria, Diego R., Manso, Luis J.
Autonomous navigation is a key skill for assistive and service robots. To be successful, robots have to minimise the disruption caused to humans while moving. This implies predicting how people will move and complying with social conventions. Avoidin
Externí odkaz:
http://arxiv.org/abs/2102.08863
In this work, we present the Chatbot Interaction with Artificial Intelligence (CI-AI) framework as an approach to the training of deep learning chatbots for task classification. The intelligent system augments human-sourced data via artificial paraph
Externí odkaz:
http://arxiv.org/abs/2010.05990
The novelty of this study consists in a multi-modality approach to scene classification, where image and audio complement each other in a process of deep late fusion. The approach is demonstrated on a difficult classification problem, consisting of t
Externí odkaz:
http://arxiv.org/abs/2007.10175
In speech recognition problems, data scarcity often poses an issue due to the willingness of humans to provide large amounts of data for learning and classification. In this work, we take a set of 5 spoken Harvard sentences from 7 subjects and consid
Externí odkaz:
http://arxiv.org/abs/2007.00659
Publikováno v:
Soft Computing 2019
In this work, we argue that the implications of Pseudo and Quantum Random Number Generators (PRNG and QRNG) inexplicably affect the performances and behaviours of various machine learning models that require a random input. These implications are yet
Externí odkaz:
http://arxiv.org/abs/1910.04701
Autonomous navigation is a key skill for assistive and service robots. To be successful, robots have to navigate avoiding going through the personal spaces of the people surrounding them. Complying with social rules such as not getting in the middle
Externí odkaz:
http://arxiv.org/abs/1909.09003
Publikováno v:
Data, Vol. 5, Num. 1, pp. 1-10, MDPI (2020)
Adapting to social conventions is an unavoidable requirement for the acceptance of assistive and social robots. While the scientific community broadly accepts that assistive robots and social robot companions are unlikely to have widespread use in th
Externí odkaz:
http://arxiv.org/abs/1909.02993
This study suggests a new approach to EEG data classification by exploring the idea of using evolutionary computation to both select useful discriminative EEG features and optimise the topology of Artificial Neural Networks. An evolutionary algorithm
Externí odkaz:
http://arxiv.org/abs/1908.04784