近年发表的第一作者论文
1. H. Lin, J. Qian and B. Di, "Learning for Adaptive Multi-Copy Relaying in Vehicular Delay Tolerant Network," in IEEE Transactions on Intelligent Transportation Systems, vol. 25, no. 3, pp. 3054-3063, March 2024(中科院1区,TOP)
2. H. Lin, Y. Han, W. Cai and B. Jin, "Traffic Signal Optimization Based on Fuzzy Control and Differential Evolution Algorithm," in IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 8, pp. 8555-8566, Aug. 2023(中科院1区,TOP)
3. Haifeng Lin, Qilin Xue, Jiayin Feng, Di Bai, Internet of things intrusion detection model and algorithm based on cloud computing and multi-feature extraction extreme learning machine, Digital Communications and Networks, Volume 9, Issue 1, 2023, Pages 111-124(中科院1区,TOP)
4. H. Lin and C. Tang, "Analysis and Optimization of Urban Public Transport Lines Based on Multiobjective Adaptive Particle Swarm Optimization," in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 9, pp. 16786-16798, Sept. 2022(中科院1区,TOP)
5. H. Lin and C. Tang, "Intelligent Bus Operation Optimization by Integrating Cases and Data Driven Based on Business Chain and Enhanced Quantum Genetic Algorithm," in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 7, pp. 9869-9882, July 2022(中科院1区,TOP)
6. Haifeng Lin, Ji Lin, Fang Wang, An innovative machine learning model for supply chain management, Journal of Innovation & Knowledge, 2022, 7(4), 10027. (中科院1区,TOP)
7. 林海峰,马宇晨,蒋玲. 基于深度学习的小目标林火检测实验设计与实现, 南京林业大学学报,2025.05(北核)
近年指导学生发表的论文
2026年:
1. Shen Y, Wang F, Qian J and Lin H(*), LE-PWDNet: a lightweight and enhanced detection framework based on DEIM for early-stage pine wilt disease. Front. Plant Sci. 16:1701009
2025年:
1. Jie Zhou, Fang Wang, Hongping Zhou and Haifeng Lin(*),PWD-Lightweight and Feature Fusion Network for Multi-Stage Joint Detection of Pine Wilt Disease, Computers and Electronics in Agriculture, 239PB (2025) 111015(中科院1区,TOP)
2. Zhichao Chen, Haifeng Lin (*), Di Bai, Jingjing Qian, Hongping Zhou, Yunya Gao, PWDViTNet: A lightweight early pine wilt disease detection model based on the fusion of ViT and CNN, Computers and Electronics in Agriculture, Volume 230:109910, 2025(中科院1区,TOP)
3. Jiajun Wang, Li Jin, Fang Wang, Hongping Zhou and Haifeng Lin(*), Hierarchical attention and feature enhancement network for multi-scale small targets in pine wilt disease,
Computers and Electronics in Agriculture, 239PB (2025) 111037(中科院1区,TOP)
4. Bai, Minhui, Xinyu Di, Lechuan Yu, Jian Ding, and Haifeng Lin (*). 2025. "A Pine Wilt Disease Detection Model Integrated with Mamba Model and Attention Mechanisms Using UAV Imagery" Remote Sensing 17, no. 2: 255.(中科院2区)
5. Gu, Yating, Yuxin Jing, Hao-Dong Li, Juntao Shi, and Haifeng Lin (*). 2025. "DEMNet: A Small Object Detection Method for Tea Leaf Blight in Slightly Blurry UAV Remote Sensing Images" Remote Sensing 17, no. 12: 1967. (中科院2区)
6. Lin Y, Xiao X and Lin H (*) YOLOv8-FDA: lightweight wheat ear detection and counting in drone images based on improved YOLOv8. Front. Plant Sci. 16:1682243.(中科院2区)
2024年:
1. Guodong Wang, Di Bai, Haifeng Lin (*), Hongping Zhou, Jingjing Qian, FireViTNet: A hybrid model integrating ViT and CNNs for forest fire segmentation, Computers and Electronics in Agriculture, 2024, 218: 108722(中科院1区,TOP)
2. Yao, Xianze, Haifeng Lin (*), Di Bai, and Hongping Zhou. 2024. "A Small Target Tea Leaf Disease Detection Model Combined with Transfer Learning" Forests 15, no. 4: 591. (中科院2区)
3. Chen, Zhichao, Hongping Zhou, Haifeng Lin (*), and Di Bai. 2024. "TeaViTNet: Tea Disease and Pest Detection Model Based on Fused Multiscale Attention" Agronomy 14, no. 3: 633.(中科院2区)
4. Wang, Guodong, Fang Wang, Hongping Zhou, and Haifeng Lin (*). 2024. "Fire in Focus: Advancing Wildfire Image Segmentation by Focusing on Fire Edges" Forests 15, no. 1: 217.(中科院2区)
5. Jin Li, Yanqi Yu, Jianing Zhou, Di Bai, Haifeng Lin (*), and Hongping Zhou. 2024. "SWVR: A Lightweight Deep Learning Algorithm for Forest Fire Detection and Recognition" Forests 15, no. 1: 204.(中科院2区)
6. 薛震洋,林海峰(*),焦万果.基于卷积神经网络的林火小目标和烟雾检测模型[J].南京林业大学学报(自然科学版),2025,49(01):225-234.(北核)
2023年:
1. Qian, J.; Bai, D.; Jiao, W.; Jiang, L.; Xu, R.; Lin, H (*).; Wang, T. A High-Precision Ensemble Model for Forest Fire Detection in Large and Small Targets. Forests 2023, 14, 2089.(中科院2区)
2. Chen, B.; Bai, D.; Lin, H (*).; Jiao, W. FlameTransNet: Advancing Forest Flame Segmentation with Fusion and Augmentation Techniques. Forests 2023, 14, 1887(中科院2区)
3. Chen, Gong, Renxi Cheng, Xufeng Lin, Wanguo Jiao, Di Bai, and Haifeng Lin (*). 2023. "LMDFS: A Lightweight Model for Detecting Forest Fire Smoke in UAV Images Based on YOLOv7" Remote Sensing 15, no. 15: 3790.(中科院2区)
4. Wang, Yinkai, Renjie Xu, Di Bai, and Haifeng Lin (*). 2023. "Integrated Learning-Based Pest and Disease Detection Method for Tea Leaves" Forests 14, no. 5: 1012.(中科院2区)
5. Qian, J.; Lin, J.; Bai, D.; Xu, R.; Lin, H (*). Omni-Dimensional Dynamic Convolution Meets Bottleneck Transformer: A Novel Improved High Accuracy Forest Fire Smoke Detection Model. Forests 2023, 14, 838.(中科院2区)
6. 王寅凯,曹磊,钱佳晨,林海峰(*). 一种改进YOLOv5的多尺度像素林火识别算法[J].林业工程学报,2023,8(02):159-165.(北核)
7. Xue, Z.; Xu, R.; Bai, D.; Lin, H (*). YOLO-Tea: A Tea Disease Detection Model Improved by YOLOv5. Forests 2023, 14, 415.(中科院2区)
8. Lin, J.; Lin, H (*).; Wang, F. A Semi-Supervised Method for Real-Time Forest Fire Detection Algorithm Based on Adaptively Spatial Feature Fusion. Forests 2023, 14, 361.(中科院2区)
9. Chen, G.; Zhou, H.; Li, Z.; Gao, Y.; Bai, D.; Xu, R.; Lin, H (*). Multi-Scale Forest Fire Recognition Model Based on Improved YOLOv5s. Forests 2023, 14, 315.(中科院2区)
10. Lin, J.; Bai, D.; Xu, R.; Lin, H (*). TSBA-YOLO: An Improved Tea Diseases Detection Model Based on Attention Mechanisms and Feature Fusion. Forests 2023, 14, 619.(中科院2区)
2022年:
1. Xue, Q.; Lin, H (*).; Wang, F. FCDM: An Improved Forest Fire Classification and Detection Model Based on YOLOv5. Forests 2022, 13, 2129.(中科院2区)
2. Qian, J.; Lin, H (*). A Forest Fire Identification System Based on Weighted Fusion Algorithm. Forests 2022, 13, 1301.(中科院2区)
3. Xue, Z.; Lin, H (*).; Wang, F. A Small Target Forest Fire Detection Model Based on YOLOv5 Improvement. Forests 2022, 13, 1332.(中科院2区)
4. Lin, J.; Lin, H (*).; Wang, F. STPM_SAHI: A Small-Target Forest Fire Detection Model Based on Swin Transformer and Slicing Aided Hyper Inference. Forests 2022, 13, 1603.(中科院2区)
发明专利(第一发明人)
1. 一种农作物病虫害防治作业多旋翼无人机,ZL202111340987.8
2. 一种基于热成像分析技术的林火识别方法、设备及计算机存储介质,ZL 202111277941.6
3. 一种对农业病虫进行防控的无人机装置,ZL202110367319.8
4. 一种农业用病虫害监测用无人机,ZL202110311495.X
5. 一种农业用病虫害防治的精量施药无人机装置,ZL202110324358X
6. 一种农作物病虫害无人机作业农药喷洒装置,ZL202111412481.3
7. 一种基于模糊推理的林火发生模型预警系统, ZL201610180341.0
8. 一种森林火灾天气指数预警系统及应用,ZL201410086682.2
9. 一种茶树种植自动化施肥处理装置,ZL202410228580.3
10. 一种针阔混交林中松材线虫病变色疫木识别方法,ZL202410735437.3
11. 一种早期松材线虫病害识别方法及识别系统,ZL 2024 1 0735408.7
12. 基于平衡参数和检测精度的早期松材线虫病害识别方法,ZL 2024 1 0737851.8
13. METHODS FOR IDENTIFYING PINE WOOD NEMATODE-INFECTED DISCOLORED WOODS IN MIXED CONIFEROUS AND BROADLEAF FORESTS, US 12,423,971 B1 (美国发明专利)
指导学生授权的发明专利
1. 一种农作物病虫害防治作业多旋翼无人机,ZL 202310633287.0
2. 一种基于无人机的农作物病虫害防治装置,ZL 202310515084.1
3. 一种农作物病虫害无人机作业农药喷洒装置,ZL 202310603117.8
4. 一种对农业病虫害进行防控的无人机装置,ZL 202310568416.2
标准(第一起草人)
1. 农业生产经营主体质量安全信用等级评价规范(DB32/T 4713-2024),江苏省地方标准
2. 农产品质量安全信用系统安全防护技术规范(DB32/T 5243-2025),江苏省地方标准