Study of Machine Learning Techniques for Plant Disease Recognition in Agriculture

被引：3
|
作者：
Dwivedi, Pallavi [1 ]
Kumar, Sumit [1 ]
Vijh, Surbhi [2 ]
Chaturvedi, Yatender [2 ]
机构：
[1] Amity Univ, Noida, Uttar Pradesh, India
[2] KIET Grp Inst, Ghaziabad, Uttar Pradesh, India
来源：
2021 11TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING, DATA SCIENCE & ENGINEERING (CONFLUENCE 2021) | 2021年
关键词：
Leaf diseases; Machine Learning; Feature extraction; image segmentation; classification; IMAGE-PROCESSING TECHNIQUES; CLASSIFICATION;
D O I：
10.1109/Confluence51648.2021.9377186
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Usage of machine learning in agriculture is showing exponential improvement and gateway for interdisciplinary research. The implementation of autonomous techniques in agriculture can help farmers to perceive the disorder in crop yields, including identification of patterns. In the horticulture field, detection of disease for plant protection and crop management perform the significant role. In this paper, the objective is to study and analyze the various disease classification methodologies, advance techniques of machine learning used by different researchers in agriculture application.
引用
收藏
页码：752 / 756
页数：5
相关论文
共 50 条
  • [1] A Review on Machine Learning Classification Techniques for Plant Disease Detection
    Shruthi, U.
    Nagaveni, V
    Raghavendra, B. K.
    [J]. 2019 5TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING & COMMUNICATION SYSTEMS (ICACCS), 2019, : 281 - 284
  • [2] A Survey on Plant Disease Prediction using Machine Learning and Deep Learning Techniques
    Gokulnath, B., V
    Devi, Usha G.
    [J]. INTELIGENCIA ARTIFICIAL-IBEROAMERICAL JOURNAL OF ARTIFICIAL INTELLIGENCE, 2020, 23 (65): : 136 - 154
  • [3] Survey on Machine Learning and Deep Learning Techniques for Agriculture Land
    Singh G.
    Sethi G.K.
    Singh S.
    [J]. SN Computer Science, 2021, 2 (6)
  • [4] MACHINE LEARNING TECHNIQUES IN PLANT DISEASE DETECTION AND CLASSIFICATION - A STATE OF THE ART
    John, Sreya
    Rose, Arul Leena
    [J]. INMATEH-AGRICULTURAL ENGINEERING, 2021, 65 (03): : 362 - 372
  • [5] Early diagnosis of rice plant disease using machine learning techniques
    Sharma, Mayuri
    Kumar, Chandan Jyoti
    Deka, Aniruddha
    [J]. ARCHIVES OF PHYTOPATHOLOGY AND PLANT PROTECTION, 2022, 55 (03) : 259 - 283
  • [6] An analysis to investigate plant disease identification based on machine learning techniques
    Duhan, Sangeeta
    Gulia, Preeti
    Gill, Nasib Singh
    Yahya, Mohammad
    Yadav, Sangeeta
    Hassan, Mohamed M.
    Alsberi, Hassan
    Shukla, Piyush Kumar
    [J]. EXPERT SYSTEMS, 2024, 41 (08)
  • [7] Towards application of various machine learning techniques in agriculture
    Jagtap, Santosh T.
    Phasinam, Khongdet
    Kassanuk, Thanwamas
    Jha, Subhesh Saurabh
    Ghosh, Tanmay
    Thakar, Chetan M.
    [J]. MATERIALS TODAY-PROCEEDINGS, 2022, 51 : 793 - 797
  • [8] Multiclass recognition of Alzheimer's and Parkinson's disease using various machine learning techniques: A study
    Balaji, Chetan
    Suresh, D. S.
    [J]. INTERNATIONAL JOURNAL OF MODELING SIMULATION AND SCIENTIFIC COMPUTING, 2022, 13 (01)
  • [9] Editorial: Machine vision and machine learning for plant phenotyping and precision agriculture
    Liu, Huajian
    Xu, Zhanyou
    [J]. FRONTIERS IN PLANT SCIENCE, 2023, 14
  • [10] Plant leaves disease detection using Image Processing and Machine learning techniques
    Kokardekar, P.
    Shah, Aman
    Thakur, Arjun
    Shahu, Prachi
    Raggad, Rohan
    Keshaowar, Sudhanshu
    Pashine, Vineet
    [J]. INTERNATIONAL JOURNAL OF NEXT-GENERATION COMPUTING, 2022, 13 (05): : 1304 - 1311
12345