Arakeri et al., 2017 - Google Patents
Computer vision based robotic weed control system for precision agricultureArakeri et al., 2017
- Document ID
- 17633214897616796194
- Author
- Arakeri M
- Kumar B
- Barsaiya S
- Sairam H
- Publication year
- Publication venue
- 2017 international conference on advances in computing, communications and informatics (ICACCI)
External Links
Snippet
India is primarily an agriculture-based country and its economy largely depends upon the agriculture. But, most of the crops grown by the farmer are affected by weeds. Weed identification and control remains one of the most challenging tasks in agriculture. The most …
- 241000196324 Embryophyta 0 title abstract description 90
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/00771—Recognising scenes under surveillance, e.g. with Markovian modelling of scene activity
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/0063—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
- G06K9/00657—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas of vegetation
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Arakeri et al. | Computer vision based robotic weed control system for precision agriculture | |
Chen et al. | An AIoT based smart agricultural system for pests detection | |
Seng et al. | Computer vision and machine learning for viticulture technology | |
Roldán-Serrato et al. | Automatic pest detection on bean and potato crops by applying neural classifiers | |
Nagar et al. | A comprehensive survey on pest detection techniques using image processing | |
Mathi et al. | An internet of things-based efficient solution for smart farming | |
CN117496356A (en) | Agricultural artificial intelligent crop detection method and system | |
Kurtser et al. | The use of dynamic sensing strategies to improve detection for a pepper harvesting robot | |
Rahman et al. | Role of artificial intelligence in pest management | |
Khatri et al. | Computer vision and image processing for precision agriculture | |
Dalai et al. | An intelligent vision based pest detection system using RCNN based deep learning mechanism | |
Martin et al. | Identification and counting of pests using extended region grow algorithm | |
Daud et al. | Detection of Oil Palm Tree and Loose Fruitlets for Fresh Fruit Bunch’s Ready-to-Harvest Prediction via Deep Learning Approach. | |
Sujatha et al. | UGVs for agri spray with AI assisted paddy crop disease identification | |
CN118446827B (en) | Pest control method for forestry tending | |
de Ocampo et al. | Integrated Weed Estimation and Pest Damage Detection in Solanum melongena Plantation via Aerial Vision-based Proximal Sensing. | |
Kumar | Survey on computational entomology: sensors based approaches to detect and classify the fruit flies | |
Negrete | Artificial vision in mexican agriculture for identification of diseases, pests and invasive plants | |
CN117148890A (en) | Temperature control system and method for applying infrared sensor to plant growth | |
Raj et al. | Machine vision based agricultural weed detection and smart herbicide spraying | |
Kamath et al. | Classification of weeds of paddy fields using deep learning | |
WO2023107023A1 (en) | Artificial intelligence based predictive decision support system in disease, pest and weed fighting | |
Ali et al. | A High Accuracy Deep Learning and Iot Network for Pest Detection Using Analysis of The Pest Sound in Large Agriculture Area | |
Patil et al. | Development of an automatic variable rate spraying system based on canopy characterization using artificial intelligence | |
Tuğrul et al. | Investigation of early detection possibilities of sugar beet disease with machine learning algorithms based on multispectral reflection |