A Soft Contrastive Learning-based Prompt Model for Few-shot Sentiment Analysis

no code implementations • 16 Dec 2023 • Jingyi Zhou, Jie zhou, Jiabao Zhao, Siyin Wang, Haijun Shan, Gui Tao, Qi Zhang, Xuanjing Huang

Few-shot text classification has attracted great interest in both academia and industry due to the lack of labeled data in many fields.

Contrastive Learning Few-Shot Text Classification +4

When Hyperspectral Image Classification Meets Diffusion Models: An Unsupervised Feature Learning Framework

no code implementations • 15 Jun 2023 • Jingyi Zhou, Jiamu Sheng, Jiayuan Fan, Peng Ye, Tong He, Bin Wang, Tao Chen

Learning effective spectral-spatial features is important for the hyperspectral image (HSI) classification task, but the majority of existing HSI classification methods still suffer from modeling complex spectral-spatial relations and characterizing low-level details and high-level semantics comprehensively.

Classification Hyperspectral Image Classification

Union-net: A deep neural network model adapted to small data sets

1 code implementation • 24 Dec 2020 • Jingyi Zhou, Qingfang He, Zhiying Lin

However, the deep neural network model has complex structure, huge model parameters, and training requires more advanced equipment, which brings certain difficulties to the application.