（1）获奖情况 （2）教学/科研项目 1.云南省基础研究专项青年项目，202401AU070159，基于视觉模型的亚洲象生物特征融合提取与自适应识别研究，2024/03-2027/02，在研，主持； 2. 昆明理工大学“双一流”重大科技专项，202302AG050009，锡治炼工业流程智能化关键技术研 究，2023/01-2026/12，在研，参与； 3. 国家自然科学基金，62076244，基于机器视觉的游泳性鱼类摄食群体特征识别与行为分析研究 ，2021/01-2024/12，已结题，参与； 4. 国家重点研发计划—政府间国际合作，2017YFE0122100，新一代水产养殖精准测控技术与智能 装备研发，2019/03-2022/02，已结题，参与。 （3）论文 1. Lian Lei(硕士生); Qiliang Yang;Ling Yang*,et.al, Deep learning implementation of image segmentation in agricultural applications: a comprehensive review, Artificial Intelligence Review, 2024, 57(6).（SCI，中科院二区，IF=11.3） 2.Ling Yang; Yingyi Chen*; Tao Shen*,et.al, A BlendMask-VoVNetV2 methodfor quantifying fish school feeding behavior in industrial aquaculture, Computers andElectronics in Agriculture, 2023, 211(108005).（SCI，中科院一区，IF=8.3） 3.Ling Yang; Huihui Yu; Yingyi Chen*, et.al, Adual attention network based on efficientNet-B2 for short-term fish school feedingbehavior analysis in aquaculture, Computers and Electronics in Agriculture, 2021,187(106316).（SCI，中科院一区，IF=8.3） 4.Ling Yang; Yeqi Liu; Yingyi Chen*,et.al, Computer Vision Models in Intelligent Aquaculture with Emphasis on Fish Detectionand Behavior Analysis: A Review, Archives of Computational Methods in Engineering, 2020,28(7).（SCI，中科院二区，IF=9.3） 5.Ling Yang; Yingyi Chen*; Tao Shen*; Daoliang Li, An FSFS-Net Method for Occluded and Aggregated Fish Segmentation from Fish School Feeding Images, APPLIED SCIENCES-BASEL, 2023, 13(10). （SCI，中科院四区，IF=2.9） 6.杨启良，陈成，雷炼，周宁珊，杨玲*.基于TD-BlendMask的复杂环境下三七叶片病害实例分割方法， 农业机械学报，2024.（EI论文） 7. Lianlei; ZilongWang;Ling Yang*, et.al, Deeplabv3+ Method for the Panax Notoginseng Disease Segmentation,2023 11th International Conference on Information Systems and Computing Technology (ISCTech),2023.（EI会议） 8. Yingyi Chen*; Huihui Liu;Ling Yang, et.al, Alightweight detection method for the spatial distributionof underwater fish schoolquantification in intensiveaquaculture,Aquaculture International, 2023, 31(1). 9. Siyuan Mei; Yingyi Chen*;Ling Yang, et.al, A Method Based on Knowledge Distillation for Fish School Stress StateRecognition in Intensive Aquaculture,CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES,2022, 131(3): 1315-1335. 10. Pan Zhang;Ling Yang; Daoliang Li*, EfficientNet-B4-Ranger: A novel method forgreenhouse cucumber disease recognition under natural complex environment, Computers and Electronics in Agriculture, 2020, 176(无): 105652. 11. Yeqi Liu; Chuanyang Gong;Ling Yang; Yingyi Chen*, DSTP-RNN: A dual-stage two-phase attention-based recurrent neural network for long-term and multivariate time seriesprediction,Expert Systems with Applications, 2020, 143: 113082. （4）知识产权 （5）专著、教材 |
