朱逢乐

浙江大学工学博士，加拿大麦吉尔大学联培博士，美国密西西比州立大学博士后；从事图像识别、嵌入式系统、深度学习、智能控制等研究，应用领域包括农业物联网、茶叶加工数字化监测、植物生长高通量感知等。先后主持浙江省“尖兵”研发攻关计划项目子课题、浙江省自然科学基金等，曾作为项目核心成员参与美国农业部与美国国际发展署的玉米黄曲霉毒素检测项目，研究成果在非洲部分地区试点推广；以第一作者或通讯作者在Engineering、Computers and Electronics in Agriculture、Chemometrics and Intelligent Laboratory Systems等国际期刊发表SCI、EI论文10余篇，多次参加ASABE、SPIE、CIGR等国际会议并作学术报告。授权发明专利5项。曾就职于互联网公司，任数据建模总监。

指导在读硕士研究生5名。

1. 丘陵山地智能高效中小型履带拖拉机研发与产业化，浙江省“尖兵”研发攻关计划项目课题，100万元，主持

2. 基于高光谱三维成像的设施作物苗期冠层生长监测机理与方法研究，浙江省自然科学基金，10万元，主持

3. 绒绣数字化图片处理软件开发，横向，10万元，主持

3. Development of rapid, non-destructive hyperspectral imaging methodology to detect and quantify fungal growth and aflatoxin contamination，美国农业部（USDA）项目，主要参与人

4. Aflagoggles for aflatoxin detection，美国国际发展署（USAID）项目，主要参与人

[1] Fengle Zhu, Zhuangfei Zhou, Yuecheng Shen, Mengzhu He, Jianuo Jiang, Xin Qiao*, Jiyu Peng*, Yong He. A 3D spectral compensation method on close-range hyperspectral imagery of plant canopies[J]. Computers and Electronics in Agriculture. 2025, 231: 109955. (SCI中科院一区, IF=7.7)

[2] Fengle Zhu, Jian Wang, Yuqian Zhang, Jiang Shi, Mengzhu He, Zhangfeng Zhao*. An improved 3D-SwinT-CNN network to evaluate the fermentation degree of black tea[J]. Food Control. 2025, 167: 110756. (SCI中科院一区, IF=5.6)

[3] Fengle Zhu, Huan Yao, Yuecheng Shen, Yuqian Zhang, Xiaoli Li, Jiang Shi, Zhangfeng Zhao*. Information fusion of hyperspectral imaging and self-developed electronic nose for evaluating the degree of black tea fermentation[J]. Journal of Food Composition and Analysis. 2025, 137: 106859. (SCI中科院二区, IF=4.0)

[4] Fengle Zhu, Yuqian Zhang, Jian Wang, Xiangdong Luo, Dengtao Liu, Kaicheng Jin, Jiyu Peng*. An improved deep convolutional generative adversarial network for quantification of catechins in fermented black tea[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy. 2025, 327: 125357. (SCI中科院二区, IF=4.3)

[5] Fengle Zhu, Xin Qiao*, Yuqian Zhang, Jiandong Jiang*. Analysis and mitigation of illumination influences on canopy close-range hyperspectral imaging for the in situ detection of chlorophyll distribution of basil crops[J]. Computers and Electronics in Agriculture. 2024, 217: 108553. (SCI中科院一区, IF=7.7)

[6] Fengle Zhu, Jian Wang, Ping Lv, Xin Qiao, Mengzhu He, Yong He, Zhangfeng Zhao*. Generating labeled samples based on improved cDCGAN for hyperspectral data augmentation: A case study of drought stress identification of strawberry leaves[J]. Computers and Electronics in Agriculture. 2024, 225: 109250. (SCI中科院一区, IF=7.7)

[7] Jiyu Peng, Longfei Ye, Yifan Liu, Fei Zhou, Linjie Xu, Fengle Zhu*, Jing Huang, Fei Liu*. Characterization of the distribution of mineral elements in chromium-stressed rice (Oryza sativa L.) leaves based on laser-induced breakdown spectroscopy and data augmentation[J]. Spectrochimica Acta Part B: Atomic Spectroscopy. 2024, 222: 107072. (SCI中科院二区, IF=3.2)

[8] Fengle Zhu^#, Zhenzhu Su^#, Alireza Sanaeifar, Anand Babu Perumal, Mostafa Gouda, Ruiqing Zhou, Xiaoli Li*, Yong He. Fingerprint spectral signatures revealing the spatiotemporal dynamics of bipolaris spot blotch progression for presymptomatic diagnosis[J]. Engineering. 2023, 22: 171-184. (SCI中科院一区，中国工程院院刊, IF=10.1)

[9] Xuelun Luo, Chanjun Sun, Yong He, Fengle Zhu*, Xiaoli Li*. Cross-cultivar prediction of quality indicators of tea based on VIS-NIR hyperspectral imaging[J]. Industrial Crops & Products. 2023, 202: 117009. (SCI中科院一区, IF=5.6)

[10] Haibo Yao*, Fengle Zhu*, Russell Kincaid, Zuzana Hruska, Kanniah Rajasekaran. A low-cost, portable device for detecting and sorting aflatoxin-contaminated maize kernels[J]. Toxins. 2023, 15(3): article ID 197. (SCI中科院二区, IF=3.9) 

[11] 朱逢乐,刘益,乔欣,何梦竹,郑增威,孙霖. 基于多尺度级联卷积神经网络的高光谱图像分析[J]. 吉林大学学报(工学版), 2023, 53(12). (EI)

[12] Fengle Zhu, Jianping Cai, Mengzhu He, Xiaoli Li*. Channel and band attention embedded 3D CNN for model development of hyperspectral image in object-scale analysis[J]. Chemometrics and Intelligent Laboratory Systems. 2022, 224: article ID 104537. (SCI中科院二区, IF=3.7)

[13] Zengwei Zheng, YiLiu, MengzhuHe, DanChen, Lin Sun, Fengle Zhu*. Effective band selection of hyperspectral image by attention mechanism-based convolutional network[J]. RSC Advances. 2022, 12(14): 8750-8759. (SCI中科院三区, IF=3.9)

[14] 朱逢乐, 严霜, 孙霖*, 何梦竹, 郑增威, 乔欣.基于深度学习多源数据融合的生菜表型参数估算方法[J].农业工程学报. 2022, 38(9): 195-204. (EI)

[15] Alireza Sanaeifar^#, Fengle Zhu^#, Junjing Sha, Xiaoli Li*, Yong He, Zhihao Zhan. Rapid quantitative characterization of tea seedlings under lead-containing aerosol particles stress using Vis-NIR spectra[J]. Science of the Total Environment. 2022, 802: article ID 149824. (SCI中科院一区, IF=8.2)

[16] Fengle Zhu, Mengzhu He, Zengwei Zheng*. Data augmentation using improved cDCGAN for plant vigor rating[J]. Computers and Electronics in Agriculture. 2020, 175: article ID 105603. (SCI中科院一区, IF=7.7)

[17] Fengle Zhu, Zengwei Zheng*. Image-based assessment of growth vigor for Phalaenopsis aphrodite seedlings using convolutional neural network[J]. 农业工程学报. 2020, 36(9): 185-194. (EI)

欢迎对图像识别、嵌入式系统、深度学习、智能控制等感兴趣的研究生、本科生加入本课题组。

招生要求：

具有较强的科研创新能力、学习主动性和团队合作精神，英语阅读和写作能力强；

熟练python、Matlab语言编程，具有嵌入式系统、图像处理和数据分析等背景优先。

联系方式：zhufl@zjut.edu.cn