主要研究领域与方向

1.  人工智能在农学中的交叉研究

2.  样本有限下的增量学习

3.  伪装物体检测

4.  基于对比学习的超细粒度视觉识别

5.  农业视频监测

2022年以来主要发表学术论著(作者、论文题目、期刊名称、发表时间、期卷页码) 
[1]Yang, SX; Zhang, LC; Lin, JW; Cernava, T; Cai, JT; Pan, RY; Liu, JM; Wen, XT; Chen, XYL; Zhang, X*(2024).LSGNet: A lightweight convolutional neural network model for tomato disease identification. CROP PROTECTION,182,106715.[中科院二区,IF=2.5,通讯作者]
[2]Lin, J., Chen, X., Cai, J., Pan, R., Cernava, T., Migheli, Q.,Zhang X.* ... & Qin, Y. (2023). Looking from shallow to deep: Hierarchical complementary networks for large scale pest identification.Computers and Electronics in Agriculture,214, 108342.[中科院一区top,IF=8.3,通讯作者]
[2] Lin, J., Chen, Y., Pan, R., Cao, T., Cai, J., Yu, D., Zhang X.* ... & Chen, X. (2022). CAMFFNet: A novel convolutional neural network model for tobacco disease image recognition. Computers and Electronics in Agriculture, 202, 107390.[中科院一区top,IF=8.3,通讯作者]
[3] Pan, R., Lin, J., Cai, J., Zhang, L., Liu, J., Wen, X., ... & Zhang, X*. (2023). A two-stage feature aggregation network for multi-category soybean leaf disease identification. Journal of King Saud University-Computer and Information Sciences, 35(8), 101669.[中科院二区,IF=6.9,通讯作者]
[4] Yu, D., Lin, J., Cao, T., Chen, Y., Li, M., & Zhang, X*. (2023). SECS: An effective CNN joint construction strategy for breast cancer histopathological image classification. Journal of King Saud University-Computer and Information Sciences, 35(2), 810-820.[中科院二区,IF=6.9,通讯作者]
[5] Cai, J., Pan, R., Lin, J., Liu, J., Zhang, L., Wen, X., ... & Zhang, X*. (2023). Improved EfficientNet for corn disease identification. Frontiers in Plant Science, 14, 1224385.[中科院二区,IF=6.8,通讯作者]
[6] Lin, J., Yu, D., Pan, R., Cai, J., Liu, J., Zhang, L., ... & Zhang, X*. (2023). Improved YOLOX-Tiny network for detection of tobacco brown spot disease. Frontiers in Plant Science, 14, 1135105.[中科院二区,IF=6.8,通讯作者]
[7] Lin, J., Chen, X., Pan, R., Cao, T., Cai, J., Chen, Y., ... & Zhang, X*. (2022). Grapenet: A lightweight convolutional neural network model for identification of grape leaf diseases. Agriculture, 12(6), 887.[中科院二区,IF=3.3,通讯作者]
[8] Chen, Y., Chen, X., Lin, J., Pan, R., Cao, T., Cai, J., ... & Zhang, X*. (2022). Dfcanet: A novel lightweight convolutional neural network model for corn disease identification. Agriculture, 12(12), 2047.[中科院二区,IF=3.3,通讯作者]
[9] 潘仁勇,张欣,陈孝玉龙等. 基于DTS-ResNet的苹果叶片病害识别方法 [J]. 国外电子测量技术, 2022, 41 (09): 142-148.[北大中文核心,通讯作者]
[10] 曹藤宝,张欣,陈孝玉龙等. 融合空间注意力机制和DenseNet的玉米病害分类方法 [J]. 无线电工程, 2022, 52 (10): 1710-1717.[北大中文核心,通讯作者]
[11] 林建吾,张欣,陈孝玉龙等. 基于轻量化卷积神经网络的番茄病害图像识别 [J]. 无线电工程, 2022, 52 (08): 1347-1353.[北大中文核心,通讯作者]
[12] 喻殿智,张欣,迟杏. 基于CA-DenseNet的乳腺癌病理图像识别 [J]. 国外电子测量技术, 2022, 41 (05): 137-143.[北大中文核心,通讯作者]
[13] 杨凯,胡圣波 & 张欣.(2023).基于Bi-LSTM及贝叶斯似然比检验的GEO与LEO卫星组合频谱感知.空间科学学报(03),567-575.[一级学报,通讯作者]
[14]  陈洋,张欣,陈孝玉龙等.CA-MobileNet V2:轻量化的作物病害识别模型[J].计算机工程与设计,2024,45(02):484-490.DOI:10.16208/j.issn1000-7024.2024.02.021. .[北大中文核心,通讯作者]

近年来指导学科竞赛代表性成果：

[1] 指导学生获“滨创杯”第九届中国研究生智慧城市技术与创意设计大赛全国一等奖及优秀指导老师(实现此赛事学校全国一等奖的突破)

[2] 指导学生获第二十届中国研究生数学建模竞赛国家级二等奖一项，国家三等奖级两项；

[3] 指导学生获第二十四届中国机器人及人工智能大赛-人工智能创新赛道全国一等奖

[4] 指导学生获第二十五届中国机器人及人工智能大赛-人工智能创新赛道全国一等奖

[5] 指导学生获2022Robocom机器人开发者大赛CAIA数字创意赛全国二等奖

[6] 指导学生获第十三届“挑战杯”贵州省大学生创业计划竞赛省级金奖

[7] 指导学生获第八届“互联网+”大学生创新创业大赛省级银奖