If you are going to #ICCV23, I recommend you check the paper by Yuanhong Chen, Fengbei Liu et al. on noisy multi-label learning applied to medical image analysis. BoMD: Bag of Multi-label Descriptors for Noisy Chest X-ray Classification

In #MICCAI23, my postdoc Hu Wang will present our recent paper on Multi-modal learning with missing modality using knowledge distillation. We have SOTA results in all benchmarks. Paper: Learnable Cross-modal Knowledge Distillation for Multi-modal Learning with Missing Modality.

In #miccai23, my postdoc Adrian Galdran will present our most recent work on model calibration using multiple classification heads, trained with different loss functions. Paper: Multi-Head Multi-Loss Model Calibration

In #ICCV23, my PhD student Chong Wang will present a new interpretable model that learns support prototypes that lie near the classification boundary, as suggested by the SVM theory. Paper: "Learning Support and Trivial Prototypes for Interpretable Image Classification"

My PhD Student Yuyuan Liu will be presenting a fascinating #ICCV23 work on #anomalydetection that improves in around 10% FPR and 7% AuPRC previous state-of-the-art in many datasets. "Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentation"

My PhD students Chong Wang and Yuanhong Chen published with #BRAIx project members, including Dr Helen Frazer, at IEEE TMI, the paper "An Interpretable and Accurate Deep-learning Diagnosis Framework Modelled with Fully and Semi-supervised Reciprocal Learning"

Nice publication by my previous PhD student, Dr Yu Tian, now a postdoc at Harvard University, with colleagues from Adelaide. The MedIA paper, is entitled "Self-supervised pseudo multi-class pre-training for unsupervised anomaly detection and segmentation in medical images".

Check out my latest article: NeurIPS'23 Paper linkedin.com/pulse/neurips2… via LinkedIn

NEW EPISODE ALERT: Will AI cure cancer? Explore the world of AI and cancer screening with Professor Carneiro and discover how AI is transforming early detection. Spotify: ow.ly/oyon50Qi5KL Apple: ow.ly/MZeC50Qi5KI #WillAIPodcast #CancerResearch @peoplecentredAI

🌟 Exciting Announcement! 🌟 I'm thrilled to share that my first fully authored textbook, "Machine Learning with Noisy Labels," has been published! 📚✨ Let's continue shaping the future of AI together. 🚀 University of Surrey Surrey Institute for People-Centred AI CVSSP Research Elsevier

CfP: At the second #MELEX workshop (in conjunction with European Conference on Computer Vision #ECCV2026 ), we will publish papers in all areas of #computervision that propose innovative models, algorithms, and ideas that show competitive results, but not necessarily the SOTA results. (1/2) sites.google.com/view/melex2024…

Joint organisation with Azade Farshad Angela Yao and Gustavo Carneiro