4 papers
Using Large Text-to-Image Models with Structured Prompts for Skin Disease Identification: A Case Study
Sajith Rajapaksa, Jean Marie Uwabeza Vianney, Renell Castro +2
This paper investigates the potential usage of large text-to-image (LTI) models for the automated diagnosis of a few skin conditions with rarity or a serious lack of annotated data…
Optimized Global Perturbation Attacks For Brain Tumour ROI Extraction From Binary Classification Models
Sajith Rajapaksa, Farzad Khalvati
Deep learning techniques have greatly benefited computer-aided diagnostic systems. However, unlike other fields, in medical imaging, acquiring large fine-grained annotated datasets…
Localized Perturbations For Weakly-Supervised Segmentation of Glioma Brain Tumours
Sajith Rajapaksa, Farzad Khalvati
Deep convolutional neural networks (CNNs) have become an essential tool in the medical imaging-based computer-aided diagnostic pipeline. However, training accurate and reliable CNN…
Crop Lodging Prediction from UAV-Acquired Images of Wheat and Canola using a DCNN Augmented with Handcrafted Texture Features
Sara Mardanisamani, Farhad Maleki, Sara Hosseinzadeh Kassani +12
Lodging, the permanent bending over of food crops, leads to poor plant growth and development. Consequently, lodging results in reduced crop quality, lowers crop yield, and makes h…