116 citations · 154 across the 13 of their papers we have counts for
14 papers
Real-time Detection of AI-Generated Speech for DeepFake Voice Conversion
Jordan J. Bird, Ahmad Lotfi
There are growing implications surrounding generative AI in the speech domain that enable voice cloning and real-time voice conversion from one individual to another. This technolo…
CIFAKE: Image Classification and Explainable Identification of AI-Generated Synthetic Images
Jordan J. Bird, Ahmad Lotfi
Recent technological advances in synthetic data have enabled the generation of images with such high quality that human beings cannot tell the difference between real-life photogra…
Robotic and Generative Adversarial Attacks in Offline Writer-independent Signature Verification
Jordan J. Bird
This study explores how robots and generative approaches can be used to mount successful false-acceptance adversarial attacks on signature verification systems. Initially, a convol…
Statistical and Spatio-temporal Hand Gesture Features for Sign Language Recognition using the Leap Motion Sensor
Jordan J. Bird
In modern society, people should not be identified based on their disability, rather, it is environments that can disable people with impairments. Improvements to automatic Sign La…
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…
Improving Customer Service Chatbots with Attention-based Transfer Learning
Jordan J. Bird
With growing societal acceptance and increasing cost efficiency due to mass production, service robots are beginning to cross from the industrial to the social domain. Currently, c…
Continuation of Famous Art with AI: A Conditional Adversarial Network Inpainting Approach
Jordan J. Bird
Much of the state-of-the-art in image synthesis inspired by real artwork are either entirely generative by filtered random noise or inspired by the transfer of style. This work exp…
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…
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,…
Probabilistic Object Classification using CNN ML-MAP layers
G. Melotti, C. Premebida, J. J. Bird +2
Deep networks are currently the state-of-the-art for sensory perception in autonomous driving and robotics. However, deep models often generate overconfident predictions precluding…
On the Effects of Pseudo and Quantum Random Number Generators in Soft Computing
Jordan J. Bird, Anikó Ekárt, Diego R. Faria
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 l…
A Deep Evolutionary Approach to Bioinspired Classifier Optimisation for Brain-Machine Interaction
Jordan J. Bird, Diego R. Faria, Luis J. Manso +2
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…