Image analysis method for identifying nutrient deficiencies in plant based on its leaf, involves specifically training CNN for a nutrient deficiency and utilizing to decide if a block is presenting any symptom of the corresponding nutrient deficiency
	HABIBA U H; LLOYD V F; KUMAR B A; KIRAN A S; SRINU A; REDDY A H V
	2023-10-16
专利权人	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
申请日期	2023-10-16
专利号	IN202341069960-A
成果简介	NOVELTY - The method involves specifically training convolutional neural network (CNN) for a nutrient deficiency and utilizing to decide if a block is presenting any symptom of the corresponding nutrient deficiency. The responses from all CNNs are integrated to produce a single response for the block. Five types of deficiencies are calcium (Ca), iron (Fe), potassium (K), magnesium (Mg), and nitrogen (N) deficiencies. A group of plants with complete nutrients are studied. A dataset with leaf images is collected and used for experimentation. USE - Image analysis method for identifying nutrient deficiencies in plant based on its leaf. ADVANTAGE - The method enables identifying nutrient deficiencies in plant based on its leaf effectively.
IPC 分类号	C05D-009/02 ; G06K-009/62 ; G06N-003/04 ; G06N-003/08 ; G06T-007/00
国家	印度
专业领域	信息技术
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/19871
专题	中国科学院新疆生态与地理研究所
作者单位	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
推荐引用方式 GB/T 7714	HABIBA U H,LLOYD V F,KUMAR B A,et al. Image analysis method for identifying nutrient deficiencies in plant based on its leaf, involves specifically training CNN for a nutrient deficiency and utilizing to decide if a block is presenting any symptom of the corresponding nutrient deficiency. IN202341069960-A[P]. 2023.

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