no code implementations • 7 Feb 2024 • Yongchen Zhou, Richard Jiang
The intersection of Artificial Intelligence (AI) and neuroscience in Explainable AI (XAI) is pivotal for enhancing transparency and interpretability in complex decision-making processes.
no code implementations • 18 Jan 2024 • Yongchen Zhou, Richard Jiang
In the domain of computer vision, the restoration of missing information in video frames is a critical challenge, particularly in applications such as autonomous driving and surveillance systems.
no code implementations • 13 Jan 2024 • Zhaonian Zhang, Richard Jiang
However, the untapped potential of Vision Transformers (ViTs), known for their accuracy and interpretability, persists in this domain due to limitations in their 3D versions.
no code implementations • 30 Oct 2023 • Luca Longo, Mario Brcic, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lecue, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Timo Speith, Simone Stumpf
As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount.
Explainable artificial intelligence Explainable Artificial Intelligence (XAI)
no code implementations • 9 Jul 2023 • Ao Shen, Yijie Zhu, Richard Jiang
Box detection assessment revealed that CBAM achieved the best outcome (F1 score of 77%) compared to coordinate attention (F1 score of 71%) and YOLOv7/bottleneck transformer (both F1 scores around 66%).
1 code implementation • 11 Oct 2022 • Abdulrahman Kerim, Felipe Chamone, Washington Ramos, Leandro Soriano Marcolino, Erickson R. Nascimento, Richard Jiang
Recent semantic segmentation models perform well under standard weather conditions and sufficient illumination but struggle with adverse weather conditions and nighttime.
1 code implementation • 26 Aug 2022 • Abdulrahman Kerim, Washington L. S. Ramos, Leandro Soriano Marcolino, Erickson R. Nascimento, Richard Jiang
In this paper, we propose a synthetic-aware adverse weather robust algorithm for video stabilization that does not require real data and can be trained only on synthetic data.
no code implementations • 25 Jun 2022 • Zhaonian Zhang, Richard Jiang, Danny Crookes, Paul Chazot
In recent years, there are various methods of estimating Biological Age (BA) have been developed.
no code implementations • 25 Jun 2022 • Ziping Jiang, Paul L. Chazot, Richard Jiang
As the bridge between genetic and physiological aspects, animal behaviour analysis is one of the most significant topics in biology and ecological research.
1 code implementation • 29 Mar 2022 • Xufeng Lin, Chang-Tsun Li, Scott Adams, Abbas Kouzani, Richard Jiang, Ligang He, Yongjian Hu, Michael Vernon, Egan Doeven, Lawrence Webb, Todd Mcclellan, Adam Guskic
As an essential prerequisite task in image-based plant phenotyping, leaf segmentation has garnered increasing attention in recent years.
no code implementations • 16 May 2021 • Richard Jiang, Paul Chazot, Danny Crookes, Ahmed Bouridane, M Emre Celebi
Facial phenotyping has recently been successfully exploited for medical diagnosis as a novel way to diagnose a range of diseases, where facial biometrics has been revealed to have rich links to underlying genetic or medical causes.
no code implementations • 12 Feb 2021 • Fredrik Wrede, Robin Eriksson, Richard Jiang, Linda Petzold, Stefan Engblom, Andreas Hellander, Prashant Singh
State-of-the-art neural network-based methods for learning summary statistics have delivered promising results for simulation-based likelihood-free parameter inference.
no code implementations • 16 Oct 2020 • Chia-Yen Chiang, Chloe Barnes, Plamen Angelov, Richard Jiang
Following the automated detection, we are able to automatically produce and calculate number of dead tree masks to label the dead trees in an image, as an indicator of forest health that could be linked to the causal analysis of environmental changes and the predictive likelihood of forest fire.
no code implementations • 16 May 2020 • Fraser Young, L. Zhang, Richard Jiang, Han Liu, Conor Wall
With the recent booming of artificial intelligence (AI), particularly deep learning techniques, digital healthcare is one of the prevalent areas that could gain benefits from AI-enabled functionality.
no code implementations • 4 May 2020 • David Lonsdale, Li Zhang, Richard Jiang
In this paper, we present our work on developing robot arm prosthetic via deep learning.
no code implementations • 27 Apr 2020 • Ranjith Dinakaran, Li Zhang, Richard Jiang
In-vehicle human object identification plays an important role in vision-based automated vehicle driving systems while objects such as pedestrians and vehicles on roads or streets are the primary targets to protect from driverless vehicles.
no code implementations • 11 Sep 2019 • Tiancheng Xia, Richard Jiang, YongQing Fu, Nanlin Jin
The approach we used in this study was based on Faster Region-based Convolutional Neural Networks (Faster RCNNs), and a transfer learning process was applied to apply this technique to the microscopic detection of blood cells.
no code implementations • 11 Sep 2019 • Khan Faraz, Ahmed Bouridane, Richard Jiang, Tiancheng Xia, Paul Chazot, Abdel Ennaceur
Gene expression of social actions in Drosophilae has been attracting wide interest from biologists, medical scientists and psychologists.
no code implementations • 5 Sep 2019 • Gary Storey, Ahmed Bouridane, Richard Jiang, Chang-Tsun Li
While facial biometrics has been widely used for identification purpose, it has recently been researched as medical biometrics for a range of diseases.
no code implementations • 21 Jul 2019 • Richard Jiang, Danny Crookes
In this paper, we propose a new computational model, namely shallow unorganized neural networks (SUNNs), in contrast to ANNs/DNNs.
no code implementations • 21 Jul 2019 • Bing Xu, Tobechukwu Agbele, Richard Jiang
The advantage of using BBC in the food logistics is clear: it can not only identify if the data or labels are authentic, but also clearly record who is responsible for the secured data or labels.
no code implementations • 31 May 2019 • Gary Storey, Richard Jiang, Shelagh Keogh, Ahmed Bouridane, Chang-Tsun Li
The capability to perform facial analysis from video sequences has significant potential to positively impact in many areas of life.
no code implementations • 29 May 2019 • Ranjith Dinakaran, Philip Easom, Li Zhang, Ahmed Bouridane, Richard Jiang, Eran Edirisinghe
In our work, GAN has been trained intensively on low resolution images, in order to neutralize the challenges of the pedestrian detection in the wild, and considered humans, and few other classes for detection in smart cities.
no code implementations • 27 Mar 2019 • Ziping Jiang, Paul L. Chazot, M. Emre Celebi, Danny Crookes, Richard Jiang
Behavioural phenotyping of Drosophila is an important means in biological and medical research to identify genetic, pathologic or psychologic impact on animal behaviour.
no code implementations • 18 Nov 2018 • Ranjith K Dinakaran, Philip Easom, Ahmed Bouridane, Li Zhang, Richard Jiang, Fozia Mehboob, Abdul Rauf
Generative adversarial networks (GANs) have been promising for many computer vision problems due to their powerful capabilities to enhance the data for training and test.