Rate My Professor Lasse Lensu

Lensu's scholarly contributions are substantial, with over 3,473 citations on Google Scholar. He is renowned for creating benchmark databases that have become standards in the field, such as the DIARETDB1 diabetic retinopathy database and evaluation protocol (2007, British Machine Vision Conference, 1,269 citations) and DIARETDB0: evaluation database and methodology for diabetic retinopathy algorithms (2006, Machine Vision and Pattern Recognition Research Group, 451 citations). Other key publications include 'Assessing the performance of deep learning models for multivariate probabilistic energy forecasting' (Applied Energy, 2021, 123 citations), 'Deep Bayesian baseline for segmenting diabetic retinopathy lesions: Advances and challenges' (Computers in Biology and Medicine, 2021, 58 citations), 'Comparison of bubble detectors and size distribution estimators' (Pattern Recognition Letters, 2018, 65 citations), 'Survey of automatic plankton image recognition: challenges, existing solutions and future perspectives' (Artificial Intelligence Review, 2024, 61 citations), and 'Performance comparison of publicly available retinal blood vessel segmentation methods' (Computerized Medical Imaging and Graphics, 2017, 59 citations). These works have advanced computer-aided diagnosis in ophthalmology, probabilistic forecasting in energy systems, and automated analysis in marine and industrial imaging, demonstrating his broad influence in computational engineering and applied AI.