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20192023
most citedA Deep Evolutionary Approach to Bioinspired Classifier Optimisation for Brain-Machine Interaction

116 citations · 154 across the 13 of their papers we have counts for

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Showing cs.CVShow all

6 papers · 1 filter

cs.CV2023★ 13 cited

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…

cs.CV2022★ 7 cited

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…

cs.CV2022

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…

cs.CV2021

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…

cs.CV2021★ 1 cited

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…

cs.CV2020

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…