2 papers
eess.IV2023
PneumoLLM: Harnessing the Power of Large Language Model for Pneumoconiosis Diagnosis
Meiyue Song, Zhihua Yu, Jiaxin Wang +11
The conventional pretraining-and-finetuning paradigm, while effective for common diseases with ample data, faces challenges in diagnosing data-scarce occupational diseases like pne…
eess.SP2023
Explainable Gated Bayesian Recurrent Neural Network for Non-Markov State Estimation
Shi Yan, Yan Liang, Le Zheng +3
The optimality of Bayesian filtering relies on the completeness of prior models, while deep learning holds a distinct advantage in learning models from offline data. Nevertheless,…