A review of deep learning techniques used in agriculture
Deep learning (DL) is a robust data-analysis and image-processing technique that has
shown great promise in the agricultural sector. In this study, 129 papers that are based on …
shown great promise in the agricultural sector. In this study, 129 papers that are based on …
Artificial intelligence, machine learning and big data in natural resources management: a comprehensive bibliometric review of literature spanning 1975–2022
Applying artificial intelligence (AI), machine learning (ML), and big data to natural resource
management (NRM) is revolutionizing how natural resources are managed. To gain more …
management (NRM) is revolutionizing how natural resources are managed. To gain more …
Sensors, systems and algorithms of 3D reconstruction for smart agriculture and precision farming: A review
S Yu, X Liu, Q Tan, Z Wang, B Zhang - Computers and Electronics in …, 2024 - Elsevier
Perceiving the shape and structure of the real three-dimensional world through sensors and
cameras is indispensable across various domains. The 3D reconstruction technology is …
cameras is indispensable across various domains. The 3D reconstruction technology is …
Tomato maturity recognition with convolutional transformers
Tomatoes are a major crop worldwide, and accurately classifying their maturity is important
for many agricultural applications, such as harvesting, grading, and quality control. In this …
for many agricultural applications, such as harvesting, grading, and quality control. In this …
YOLOv5s-CBAM-DMLHead: A lightweight identification algorithm for weedy rice (Oryza sativa f. spontanea) based on improved YOLOv5
C Yuan, T Liu, F Gao, R Zhang, X Seng - Crop Protection, 2023 - Elsevier
Rice (Oryza sativa L.) is one of the essential food sources for people, with rice farms
producing about 480 million tons of refined rice annually. In recent years, with the …
producing about 480 million tons of refined rice annually. In recent years, with the …
Advancing common bean (Phaseolus vulgaris L.) disease detection with YOLO driven deep learning to enhance agricultural AI
Common beans (CB), a vital source for high protein content, plays a crucial role in ensuring
both nutrition and economic stability in diverse communities, particularly in Africa and Latin …
both nutrition and economic stability in diverse communities, particularly in Africa and Latin …
Applications of imaging systems for the assessment of quality characteristics of bread and other baked goods: A review
One of the most widely researched topics in the food industry is bread quality analysis.
Different techniques have been developed to assess the quality characteristics of bakery …
Different techniques have been developed to assess the quality characteristics of bakery …
Estimation of the extent of the vulnerability of agriculture to climate change using analytical and deep-learning methods: a case study in Jammu, Kashmir, and Ladakh
Climate stress poses a threat to the agricultural sector, which is vital for both the economy
and livelihoods in general. Quantifying its risk to food security, livelihoods, and sustainability …
and livelihoods in general. Quantifying its risk to food security, livelihoods, and sustainability …
[HTML][HTML] Exploration of machine learning approaches for automated crop disease detection
In the era of frequently changing climatic conditions along with ever increasing world
population, it becomes imperative to ensure food security. The burden of biotic stresses …
population, it becomes imperative to ensure food security. The burden of biotic stresses …
[HTML][HTML] Strawberry ripeness detection using deep learning models
Z Mi, WQ Yan - Big Data and Cognitive Computing, 2024 - mdpi.com
In agriculture, the timely and accurate assessment of fruit ripeness is crucial to optimizing
harvest planning and reduce waste. In this article, we explore the integration of two cutting …
harvest planning and reduce waste. In this article, we explore the integration of two cutting …