Congratulations to Afees who successfully defended his thesis entitled “ENSEMBLE LEARNING FOR OPTIMAL CLUSTER ESTIMATION” last week!
Congratulations to Dima Alattal and Ferdoos Nezhad for their presentations at IEEE CBMS in L’Aquila, Italy this week!
Congratulations to Asal Azar for her talk (to 200 people!) and to Barbara Draghi and Ylenia Rotalinti for presenting their posters at a packed AIME 2023 conference.
Congratulations to Awad who successfully defended his thesis entitled “Combined Supervised and Unsupervised Learning to Identify Subclasses of Disease for Better Prediction” in January. Thanks to examiners Jaakko Hollmen and Stasha Lauria.
Biraja successfully defended his thesis, titled “When the Machine Does Now Know Measuring Uncertainty in Deep Learning Models of Medical Image” on 9th September.
Toyah Overton presented and Juliana Branescu discussed her poster at the first in-person conference for a while in Rennes, France.
Congratulations to those with new publications!:
Toyah Overton, Allan Tucker, Tim James and Dimitar Hristozov. dunXai: DO-U-Net for Explainable (Multi-Label) Image Classification, Intelligent Data Analysis Symposium 2022;
Ghoshal, B., Hikmet, F., Pineau, C., Tucker, A. and Lindskog, C. (2021) ‘DeepHistoClass: A novel strategy for confident classification of immunohistochemistry images using Deep Learning‘. Molecular & Cellular Proteomics, 0 (In Press). pp. 1 – 71. ISSN: 1535-9476
Barnaby E. Walker, Allan Tucker and Nicky Nicolson, Harnessing Large-Scale Herbarium Image Datasets Through Representation Learning, Front. Plant Sci., 13 January 2022 | https://doi.org/10.3389/fpls.2021.806407
Congratulations to the following for their recent paper acceptance!
Biraja Ghoshal and Allan Tucker, “On Cost-Sensitive Calibrated Uncertainty in Deep Learning: An application on COVID-19 detection” to IEEE CBMS 2021
Seyed Erfan Sajjadi and Allan Tucker, “Exploiting Clinical Staging Data to Constrain Pseudo-Time Modelling of Disease Progression” to IEEE CBMS 2021
Ben Evans and Allan Tucker
Evans B.C., Tucker A., Wearn O.R., Carbone C. (2021). Reasoning About Neural Network Activations: An Application in Spatial Animal Behaviour from Camera Trap Classifications. In: Koprinska I. et al. (eds) ECML PKDD 2020 Workshops. ECML PKDD 2020. Communications in Computer and Information Science, vol 1323. Springer, Cham. https://doi.org/10.1007/978-3-030-65965-3_2
Zhihao Dai, Zhong Li and Lianghao Han. (2021). BoneBert: A BERT-based Automated Information Extraction System of Radiology Reports for Bone Fracture Detection and Diagnosis, IDA 2021.
Yue Shi, Liangxiu Han, Wenjiang Huang, Sheng Chang, Yingying Dong, Darren Dancey, Lianghao Han. (2021). A Biologically Interpretable Two-stage Deep Neural Network (BIT-DNN) For Vegetation Recognition From Hyperspectral Imagery, 10.1109/TGRS.2021.3058782, IEEE Transactions on Geoscience and Remote Sensing, IDA 2021.
Biraja Ghoshal and Allan Tucker
Ghoshal, B. and Tucker, A. (2021) Hyperspherical Weight Uncertainty in Neural Networks, IDA 2021.
Bjaveet Nagaria, Ben Evans, Ashley Mann and Mahir Arzoky (2021). ‘Using an Instant Visual and Text Based Feedback_Tool to Teach Path Finding Algorithms A Concept’.SEENG 2021 Third International Workshop on Software Engineering Education for the Next Generation. Virtual.
Biraja Ghoshal, Bhargab Ghoshal, Stephen Swift, Allan Tucker (2021). “Uncertainty Estimation in SARS-CoV-2 B-cell Epitope Prediction for Vaccine Development”, AIME 2021
Biraja Ghoshal, Stephen Swift, Allan Tucker (2021). Bayesian Deep Active Learning for Medical Image Analysis, AIME 2021
The IDA- Group gave a talk at the inaugaural workshop by the HDR UK Synthetic Data Special Interest Group:
Congratulations Yani Xue for successfully defending here thesis titled “Effective and Efficient Evolutionary Many-Objective Optimization”