4 papers · 1 filter
Improving Predictive Confidence in Medical Imaging via Online Label Smoothing
Kushan Choudhury, Shubhrodeep Roy, Ankur Chanda +2
Deep learning models, especially convolutional neural networks, have achieved impressive results in medical image classification. However, these models often produce overconfident…
Evaluating Temperature Scaling Calibration Effectiveness for CNNs under Varying Noise Levels in Brain Tumour Detection
Ankur Chanda, Kushan Choudhury, Shubhrodeep Roy +2
Precise confidence estimation in deep learning is vital for high-stakes fields like medical imaging, where overconfident misclassifications can have serious consequences. This work…
An ensemble framework approach of hybrid Quantum convolutional neural networks for classification of breast cancer images
Dibyasree Guha, Shyamali Mitra, Somenath Kuiry +1
Quantum neural networks are deemed suitable to replace classical neural networks in their ability to learn and scale up network models using quantum-exclusive phenomena like superp…
Regularizing CNNs using Confusion Penalty Based Label Smoothing for Histopathology Images
Somenath Kuiry, Alaka Das, Mita Nasipuri +1
Deep Learning, particularly Convolutional Neural Networks (CNN), has been successful in computer vision tasks and medical image analysis. However, modern CNNs can be overconfident,…