Artificial Intelligence

These two datasets are significantly different from each other in terms of the image color, cell shape, background, etc., which can better evaluate the robustness of WBC segmentation approach. The ground truth segmentation results are manually sketched by domain experts, where the nuclei, cytoplasms and background including red blood cells are marked in white, gray and black respectively. We also submitted the segmentation results by our approach, where the whole WBC region are marked in white and the others are marked in black.

We consider the automation of polishing process for manufactured components, which is typically an iterative, multi-stage process that depends heavily on the practitioner’s expertise and visual inspection to guide decisions on polishing pad changes and fine-tuning of control parameters. We use a model-free, on-policy actor-critic reinforcement learning (RL) algorithm to determine the choice of pad, downforce, rotational speed, polishing duration for each stage, and the total number of polishing / inspection stages.

With the rapid advancement of large language models (LLMs), Model-as-a-Service (MaaS) has emerged as a powerful paradigm, enabling providers to deliver pre-trained models, computational resources, and database management within a unified platform.

The Fuyong dataset records 134 stroke patients who received treatment in the Shenzhen Fuyong People's Hospital between March 1, 2022, and September 31, 2024. Besides, medical records of 435 stroke patients treated in the Affiliated Taizhou People's Hospital of Nanjing Medical University between January 1, 2020, and December 31, 2023, are included in the Taizhou dataset. These two datasets use the pre- and post-thrombolysis of the NIHSS scores as a metric for evaluating the immediate efficacy of the thrombolytic intervention.