no code implementations • 17 Oct 2022 • Isaac Ronald Ward, Charles Moore, Kai Pak, Jingdao Chen, Edwin Goh
In this study, we propose two approaches to resolve this: 1) an unsupervised deep clustering step on the Mars datasets, which identifies clusters of images containing similar semantic content and corrects false negative errors during training, and 2) a simple approach which mixes data from different domains to increase visual diversity of the total training dataset.
no code implementations • 25 Dec 2021 • Isaac Ronald Ward, Ling Wang, Juan lu, Mohammed Bennamoun, Girish Dwivedi, Frank M Sanfilippo
Using XAI, we quantified the contribution that specific drugs had on these ACS predictions, thus creating an XAI-based technique for pharmacovigilance monitoring, using ACS as an example of the adverse outcome to detect.
Explainable artificial intelligence Explainable Artificial Intelligence (XAI) +1
1 code implementation • 11 Oct 2020 • Isaac Ronald Ward, Jack Joyner, Casey Lickfold, Yulan Guo, Mohammed Bennamoun
Graph neural networks (GNNs) have recently grown in popularity in the field of artificial intelligence (AI) due to their unique ability to ingest relatively unstructured data types as input data.
no code implementations • 22 Jul 2019 • Isaac Ronald Ward, Hamid Laga, Mohammed Bennamoun
Deep learning techniques, coupled with the availability of large training datasets, have now revolutionized the field of computer vision, including RGB-D object detection, achieving an unprecedented level of performance.
no code implementations • 28 Apr 2019 • Isaac Ronald Ward, M. A. Asim K. Jalwana, Mohammed Bennamoun
This work investigates the impact of the loss function on the performance of Neural Networks, in the context of a monocular, RGB-only, image localization task.
no code implementations • 25 Apr 2019 • Benjamin Allaert, Isaac Ronald Ward, Ioan Marius Bilasco, Chaabane Djeraba, Mohammed Bennamoun
Optical flow techniques are becoming increasingly performant and robust when estimating motion in a scene, but their performance has yet to be proven in the area of facial expression recognition.