1 citations · 3 across the 6 of their papers we have counts for
11 papers
Reducing Overconfidence Predictions for Autonomous Driving Perception
Gledson Melotti, Cristiano Premebida, Jordan J. Bird +2
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…
Fruit Quality and Defect Image Classification with Conditional GAN Data Augmentation
Jordan J. Bird, Chloe M. Barnes, Luis J. Manso +2
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…
A Graph Neural Network to Model Disruption in Human-Aware Robot Navigation
Pilar Bachiller, Daniel Rodriguez-Criado, Ronit R. Jorvekar +3
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 predicti…
Chatbot Interaction with Artificial Intelligence: Human Data Augmentation with T5 and Language Transformer Ensemble for Text Classification
Jordan J. Bird, Anikó Ekárt, Diego R. Faria
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. Th…
Look and Listen: A Multi-modality Late Fusion Approach to Scene Classification for Autonomous Machines
Jordan J. Bird, Diego R. Faria, Cristiano Premebida +2
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…
LSTM and GPT-2 Synthetic Speech Transfer Learning for Speaker Recognition to Overcome Data Scarcity
Jordan J. Bird, Diego R. Faria, Anikó Ekárt +2
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,…