Chaitanya Kaul

According to our database, Chaitanya Kaul authored at least 23 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

AI-Enabled Sensor Fusion of Time-of-Flight Imaging and mmWave for Concealed Metal Detection.

Chaitanya Kaul, Kevin J. Mitchell, Khaled Kassem, Athanasios Tragakis, Valentin Kapitany, Ilya Starshynov, Federica A. Villa, Roderick Murray-Smith, Daniele Faccio

Sensors, September, 2024

Computational limits to the legibility of the imaged human brain.

James K. Ruffle, Robert J. Gray, Samia Mohinta, Guilherme Pombo, Chaitanya Kaul, Harpreet Hyare, Geraint Rees, Parashkev Nachev

NeuroImage, 2024

Is One GPU Enough? Pushing Image Generation at Higher-Resolutions with Foundation Models.

Athanasios Tragakis, Marco Aversa, Chaitanya Kaul, Roderick Murray-Smith, Daniele Faccio

CoRR, 2024

Glfnet: Global-Local (Frequency) Filter Networks for Efficient Medical Image Segmentation.

Athanasios Tragakis, Qianying Liu, Chaitanya Kaul, Swalpa Kumar Roy, Hang Dai, Fani Deligianni, Roderick Murray-Smith, Daniele Faccio

Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

HpEIS: Learning Hand Pose Embeddings for Multimedia Interactive Systems.

Songpei Xu, Xuri Ge, Chaitanya Kaul, Roderick Murray-Smith

Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

2023

Survey: Leakage and Privacy at Inference Time.

Marija Jegorova, Chaitanya Kaul, Charlie Mayor, Alison Q. O'Neil, Alexander Weir, Roderick Murray-Smith, Sotirios A. Tsaftaris

IEEE Trans. Pattern Anal. Mach. Intell., July, 2023

The legibility of the imaged human brain.

James K. Ruffle, Robert J. Gray, Samia Mohinta, Guilherme Pombo, Chaitanya Kaul, Harpreet Hyare, Geraint Rees, Parashkev Nachev

CoRR, 2023

The Fully Convolutional Transformer for Medical Image Segmentation.

Athanasios Tragakis, Chaitanya Kaul, Roderick Murray-Smith, Dirk Husmeier

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Continuous Interaction with A Smart Speaker via Low-Dimensional Embeddings of Dynamic Hand Pose.

Songpei Xu, Chaitanya Kaul, Xuri Ge, Roderick Murray-Smith

Proceedings of the IEEE International Conference on Acoustics, 2023

mmSense: Detecting Concealed Weapons with a Miniature Radar Sensor.

Kevin J. Mitchell, Khaled Kassem, Chaitanya Kaul, Valentin Kapitany, Philip Binner, Andrew Ramsay, Daniele Faccio, Roderick Murray-Smith

Proceedings of the IEEE International Conference on Acoustics, 2023

Optimizing Vision Transformers for Medical Image Segmentation.

Qianying Liu, Chaitanya Kaul, Jun Wang, Christos Anagnostopoulos, Roderick Murray-Smith, Fani Deligianni

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Convolutional Point Transformer.

Chaitanya Kaul, Joshua Mitton, Hang Dai, Roderick Murray-Smith

Proceedings of the Computer Vision - ACCV 2022 Workshops, 2022

2021

Rotation Equivariant 3D Hand Mesh Generation from a Single RGB Image.

Joshua Mitton, Chaitanya Kaul, Roderick Murray-Smith

CoRR, 2021

CpT: Convolutional Point Transformer for 3D Point Cloud Processing.

Chaitanya Kaul, Joshua Mitton, Hang Dai, Roderick Murray-Smith

CoRR, 2021

Prediction of weaning from mechanical ventilation using Convolutional Neural Networks.

Yan Jia, Chaitanya Kaul, Tom Lawton, Roderick Murray-Smith, Ibrahim Habli

Artif. Intell. Medicine, 2021

Focusnet++: Attentive Aggregated Transformations For Efficient And Accurate Medical Image Segmentation.

Chaitanya Kaul, Nick E. Pears, Hang Dai, Roderick Murray-Smith, Suresh Manandhar

Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

2020

FatNet: A Feature-attentive Network for 3D Point Cloud Processing.

Chaitanya Kaul, Nick E. Pears, Suresh Manandhar

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Penalizing Small Errors Using an Adaptive Logarithmic Loss.

Chaitanya Kaul, Nick E. Pears, Hang Dai, Roderick Murray-Smith, Suresh Manandhar

Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020

2019

Models of visual attention in deep residual CNNs

Chaitanya Kaul

PhD thesis, 2019

Divided We Stand: A Novel Residual Group Attention Mechanism for Medical Image Segmentation.

Chaitanya Kaul, Nick E. Pears, Suresh Manandhar

CoRR, 2019

Penalizing small errors using an Adaptive Logarithmic Loss.

Chaitanya Kaul, Nick E. Pears, Suresh Manandhar

CoRR, 2019

SAWNet: A Spatially Aware Deep Neural Network for 3D Point Cloud Processing.

Chaitanya Kaul, Nick E. Pears, Suresh Manandhar

CoRR, 2019

Focusnet: An Attention-Based Fully Convolutional Network for Medical Image Segmentation.

Chaitanya Kaul, Suresh Manandhar, Nick E. Pears

Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019