4 papers · 1 filter
Reducing Domain Gap with Diffusion-Based Domain Adaptation for Cell Counting
Mohammad Dehghanmanshadi, Wallapak Tavanapong
Generating realistic synthetic microscopy images is critical for training deep learning models in label-scarce environments, such as cell counting with many cells per image. Howeve…
CountXplain: Interpretable Cell Counting with Prototype-Based Density Map Estimation
Abdurahman Ali Mohammed, Wallapak Tavanapong, Catherine Fonder +1
Cell counting in biomedical imaging is pivotal for various clinical applications, yet the interpretability of deep learning models in this domain remains a significant challenge. W…
CellFMCount: A Fluorescence Microscopy Dataset, Benchmark, and Methods for Cell Counting
Abdurahman Ali Mohammed, Catherine Fonder, Ying Wei +4
Accurate cell counting is essential in various biomedical research and clinical applications, including cancer diagnosis, stem cell research, and immunology. Manual counting is lab…
Is Large Language Model Performance on Reasoning Tasks Impacted by Different Ways Questions Are Asked?
Seok Hwan Song, Mohna Chakraborty, Qi Li +1
Large Language Models (LLMs) have been evaluated using diverse question types, e.g., multiple-choice, true/false, and short/long answers. This study answers an unexplored question…