个人简介
2000年获重庆大学学士学位；2003年获重庆大学硕士学位；2008年获新加坡南洋理工大学博士学位。2009年至2010年获美国国家实验室基金资助在美国匹兹堡大学从事博士后研究。2011年至今在重庆大学任教。
王品副教授主要从事人工智能理论与应用、智能感知与数据科学、多模态智能感知与识别等方面理论和实验研究。近年来承担了国际合作、国家自然科学基金等科研项目十余项；在Information Sciences, Biomedical Signal Processing and Control, Digital Signal Processing, Optical letters等国内外主流期刊会议上发表了科研论文70余篇，其中二区及以上权威期刊论文30余篇，被引用累计3000余次；申请及授权国家发明专利30余项。
研究领域
方向1：智能信息处理与模式识别
方向2：数据融合与分析
方向3：人工智能与健康信息学
方向4：人工智能与模式识别
方向5：生物医学信号与信息处理
近期论文
查看导师新发文章
（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）
[1] Pin Wang*, Gongxin Yang, Yongming Li, Pufei Li, Yurou Guo, Rui Chen, Deep sample clustering domain adaptation for breast histopathology image classification，Biomedical Signal Processing and Control，2024，87：105500.（二区）
[2] Fan Li, Bo Wang, Pin Wang*, Mingfeng Jiang, Yongming Li*. An imbalanced ensemble learning method based on dual clustering and stage-wise hybrid sampling. Applied Intelligence,2023, 53: 21167-21191 （二区）
[3] Li Y, Xu J, Wang P*, Li P, Yang G, Chen R. Manifold reconstructed semi-supervised domain adaptation for histopathology images classification[J]. Biomedical Signal Processing and Control, 2023, 81: 104495-104504. （二区）
[4] Pin Wang*, Pufei Li, Yongming Li, Jin Xu, Fang Yan, Mingfeng Jiang, Deep manifold feature fusion for classification of breast histopathology images, Digital Signal Processing, 2022, 123: 103400.（二区）
[5] Pin Wang*, Pufei Li, Yongming Li, Jin Xu, Mingfeng Jiang, Classification of histopathological whole slide images based on multiple weighted semi-supervised domain adaptation, Biomedical Signal Processing and Control, 2022,73:103400.（二区）
[6] Wang P* , Li P , Li Y , et al. Histopathological image classification based on cross-domain deep transferred feature fusion[J]. Biomedical Signal Processing and Control, 2021, 68:102705. （二区）
[7] Pin Wang*, Jiaxin Wang, Yongming Li, Pufei Li, Linyu Li, Mingfeng Jiang, Automatic classification of breast cancer histopathological images based on deep feature fusion and enhanced routing, Biomedical Signal Processing and Control, 2021,65:102341.（二区）
[8] Wang P* , Li P , Yin M , et al. Burn wound assessment system using near-infrared hyperspectral imaging and deep transfer features[J]. Infrared Physics & Technology, 2020, 111:103558. （二区）
[9] Wang Pin*, Song Qi, Li Yongming, Lv Shanshan, Wang Jiaxin, Li Linyu, Zhang HeHua, Cross-task extreme learning machine for breast cancer image classification with deep convolutional features, Biomedical Signal Processing and Control, 2020, 57:101789. （二区）
[10] Wang P*, Wang L , Li Y M , et al. Automatic cell nuclei segmentation and classification of cervical Pap smear images[J]. Biomedical Signal Processing and Control, 2019, 48:93-103. （二区）
[11] Pin Wang*, Yao Cao, Meifang Yin, Yongming Li, Shanshan Lv, Lixian Huang, Dayong Zhang, Yongquan Luo, and Jun Wu.Full-field burn depth detection based on near-infrared hyperspectral imaging and ensemble regression. Review of Scientific Instrument, 2019, 90:064103. （三区）
[12] Wang P*, Xu S , Li Y M , et al. Feature-based analysis of cell nuclei structure for classification of histopathological images[J]. Digital Signal Processing, 2018, 78:152-162. （二区）
[13] Wang P*, Wang J , Wang L , et al. Classification of pathogenic bacteria using near-Infrared diffuse reflectance spectroscopy[J]. Journal of Applied Spectroscopy, 2019, 85(6):1029-1036. （三区）
[14] Wang P*, Cao Y, Li Y M, et al. A burn depth detection system based on near infrared spectroscopy and ensemble learning [J]. Review of Scientific Instruments, 2017, 88(11):114302. （三区）
[15] Wang P*, Cao Y, Li Y M, et al. Optical detection of wound infection in vivo by near infrared diffuse reflectance spectroscopy[J]. Spectroscopy Letters, 2017,50(10):566-571. （三区）
[16] Pin Wang*，Sha Xu，Yongming Li，Jie Wang，Shujun Liu. Hyperspectral image classification based on joint sparsity model with low-dimensional spectral–spatial features[J]. Journal of Applied Remote Sensing, 2017, 11(1):015010. （三区）
[17]Pin Wang*, Yongming Li, Bohan Chen, et al. Proportional hybrid mechanism for population based feature selection algorithm[J]. International Journal of Information Technology & Decision Making, 2017,16(5): 1309-1338. （二区）
[18] Wang P*, Hu X, Li Y M, et al. Automatic cell nuclei segmentation and classification of breast cancer histopathology images[J]. Signal Processing, 2016, 122(9-10):1-13. （二区）
京公网安备 11010802027423号