Implementation of artificial intelligence in agriculture for optimisation of irrigation and application of pesticides and herbicides
2020
Agriculture plays a significant role in the economic sector. The automation in agriculture is the main concern and the emerging subject across the world. The population is increasing tremendously and...
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A comprehensive review on automation in agriculture using artificial intelligence
June 2019
Agriculture automation is the main concern and emerging subject for every country. The world population is increasing at a very fast rate and with increase in population the need for food increases...
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Review of agricultural IoT technology
2022
Agricultural Internet of Things (IoT) has brought new changes to agricultural production. It not only increases agricultural output but can also effectively improve the quality of agricultural products,...
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Automation and digitization of agriculture using artificial intelligence and internet of things
2021
The growing population and effect of climate change have put a huge responsibility on the agriculture sector to increase food-grain production and productivity. In most of the countries where the expansion...
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Real-time hyperspectral imaging for the in-field estimation of strawberry ripeness with deep learning
2020
Strawberry is one of the popular fruits with numerous nutrients. The ripeness of this fruits was estimated using the hyperspectral imaging (HSI) system in field and laboratory conditions in this study....
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A review of imaging techniques for plant disease detection
2020
Agriculture is the basis of every economy worldwide. Crop production is one of the major factors affecting domestic market condition in any country. Agricultural production is also a major prerequisite...
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Applications of electronic nose (e-nose) and electronic tongue (e-tongue) in food quality-related properties determination: A review
2020
An e-nose or an e-tongue is a group of gas sensors or chemical sensors that simulate human nose or human tongue. Both e-nose and e-tongue have shown great promise and utility in improving assessments...
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Fruit ripeness classification: A survey
March 2023
Fruit is a key crop in worldwide agriculture feeding millions of people. The standard supply chain of fruit products involves quality checks to guarantee freshness, taste, and, most of all, safety....
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Deep learning based computer vision approaches for smart agricultural applications
2022
The agriculture industry is undergoing a rapid digital transformation and is growing powerful by the pillars of cutting-edge approaches like artificial intelligence and allied technologies. At the core...
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DeepRice: A deep learning and deep feature based classification of Rice leaf disease subtypes
March 2024
Rice stands as a crucial staple food globally, with its enduring sustainability hinging on the prompt detection of rice leaf diseases. Hence, efficiently detecting diseases when they have already occurred...
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Transfer Learning for Multi-Crop Leaf Disease Image Classification using Convolutional Neural Network VGG
2022
In recent times, the use of artificial intelligence (AI) in agriculture has become the most important. The technology adoption in agriculture if creatively approached. Controlling on the diseased leaves...
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How artificial intelligence uses to achieve the agriculture sustainability: Systematic review
June 2023
The generation of food production that meets the rising demand for food and ecosystem security is a big challenge. With the development of Artificial Intelligence (AI) models, there is a growing need...
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Comparison of CNN-based deep learning architectures for rice diseases classification
September 2023
Although convolutional neural network (CNN) paradigms have expanded to transfer learning and ensemble models from original individual CNN architectures, few studies have focused on the performance comparison...
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Plant disease detection using hybrid model based on convolutional autoencoder and convolutional neural network
2021
Plants are susceptive to various diseases in their growing phases. Early detection of diseases in plants is one of the most challenging problems in agriculture. If the diseases are not identified in...
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Deep convolutional neural network models for weed detection in polyhouse grown bell peppers
2022
Conventional weed management approaches are inefficient and non-suitable for integration with smart agricultural machinery. Automatic identification and classification of weeds can play a vital role...
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Examining the interplay between artificial intelligence and the agri-food industry
2022
Artificial intelligence (AI) has advanced at an astounding rate and transformed numerous economic sectors. Nevertheless, a comprehensive understanding of how AI can improve the agri-food industry is...
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Machine learning in nutrient management: A review
September 2023
In agriculture, precise fertilization and effective nutrient management are critical. Machine learning (ML) has recently been increasingly used to develop decision support tools for modern agricultural...
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A systematic review of machine learning techniques for cattle identification: Datasets, methods and future directions
2022
Increased biosecurity and food safety requirements may increase demand for efficient traceability and identification systems of livestock in the supply chain. The advanced technologies of machine learning...
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A review on computer vision systems in monitoring of poultry: A welfare perspective
2020
Monitoring of poultry welfare-related bio-processes and bio-responses is vital in welfare assessment and management of welfare-related factors. With the current development in information technologies,...
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Machine learning for weed–plant discrimination in agriculture 5.0: An in-depth review
December 2023
Agriculture 5.0 is an emerging concept where sensors, big data, Internet-of-Things (IoT), robots, and Artificial Intelligence (AI) are used for agricultural purposes. Different from Agriculture 4.0,...
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Artificial cognition for applications in smart agriculture: A comprehensive review
2020
Agriculture contributes to 6.4% of the entire world's economic production. In at least nine countries of the world, agriculture is the dominant sector of the economy. Agriculture not only provides the...
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Vision Intelligence for Smart Sheep Farming: Applying Ensemble Learning to Detect Sheep Breeds
March 2024
The ability to automatically recognize sheep breeds holds significant value for the sheep industry. Sheep farmers often require breed identification to assess the commercial worth of their flocks. However,...
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Explainable artificial intelligence and interpretable machine learning for agricultural data analysis
2022
Artificial intelligence and machine learning have been increasingly applied for prediction in agricultural science. However, many models are typically black boxes, meaning we cannot explain what the...
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Crop diagnostic system: A robust disease detection and management system for leafy green crops grown in an aquaponics facility
December 2023
Crops grown on aquaponics farms are susceptible to various diseases or biotic stresses during their growth cycle, just like traditional agriculture. The early detection of diseases is crucial to witnessing...
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Automated quality inspection of baby corn using image processing and deep learning
March 2024
The food industry typically relies heavily on manual operations with high proficiency and skills. According to the quality inspection process, a baby corn with black marks or blemishes is considered...
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