Review of the state of the art of deep learning for plant diseases: A broad analysis and discussion

RI Hasan, SM Yusuf, L Alzubaidi - Plants, 2020 - mdpi.com
Deep learning (DL) represents the golden era in the machine learning (ML) domain, and it
has gradually become the leading approach in many fields. It is currently playing a vital role …

Recent advancements and challenges of AIoT application in smart agriculture: A review

HK Adli, MA Remli, KNS Wan Salihin Wong, NA Ismail… - Sensors, 2023 - mdpi.com
As the most popular technologies of the 21st century, artificial intelligence (AI) and the
internet of things (IoT) are the most effective paradigms that have played a vital role in …

Smart agriculture applications using deep learning technologies: A survey

M Altalak, M Ammad uddin, A Alajmi, A Rizg - Applied Sciences, 2022 - mdpi.com
Agriculture is considered an important field with a significant economic impact in several
countries. Due to the substantial population growth, meeting people's dietary needs has …

sCrop: A novel device for sustainable automatic disease prediction, crop selection, and irrigation in Internet-of-Agro-Things for smart agriculture

V Udutalapally, SP Mohanty, V Pallagani… - IEEE Sensors …, 2020 - ieeexplore.ieee.org
Agriculture Cyber-Physical System (A-CPS) is becoming increasingly important in
enhancing crop quality and productivity by utilizing minimum cropland. This paper …

A survey on deep learning and its impact on agriculture: Challenges and opportunities

M Albahar - Agriculture, 2023 - mdpi.com
The objective of this study was to provide a comprehensive overview of the recent
advancements in the use of deep learning (DL) in the agricultural sector. The author …

Deep Learning model of sequential image classifier for crop disease detection in plantain tree cultivation

M Nandhini, KU Kala, M Thangadarshini… - … and Electronics in …, 2022 - Elsevier
Plantain tree is the most popular crop grown all over the world and banana (Musa spp.) is
the most marketable fruit. It is the leading food in many countries, especially in developing …

Image-based wheat fungi diseases identification by deep learning

MA Genaev, ES Skolotneva, EI Gultyaeva, EA Orlova… - Plants, 2021 - mdpi.com
Diseases of cereals caused by pathogenic fungi can significantly reduce crop yields. Many
cultures are exposed to them. The disease is difficult to control on a large scale; thus, one of …

A comprehensive survey on IoT and AI based applications in different pre-harvest, during-harvest and post-harvest activities of smart agriculture

RK Kasera, S Gour, T Acharjee - Computers and Electronics in Agriculture, 2024 - Elsevier
Today farmers around the world are gradually embracing Smart farming assisted by different
cutting-edge technologies. The Internet of Things (IoT) is playing a major role in the …

Everything you wanted to know about smart agriculture

A Mitra, SLT Vangipuram, AK Bapatla… - arXiv preprint arXiv …, 2022 - arxiv.org
The world population is anticipated to increase by close to 2 billion by 2050 causing a rapid
escalation of food demand. A recent projection shows that the world is lagging behind …

Future food production prediction using AROA based hybrid deep learning model in agri-sector

S Baswaraju, VU Maheswari, K Chennam… - Human-Centric …, 2023 - Springer
Policymaking and administration of national tactics of action for food security rely heavily on
advances in models for accurate estimation of food output. In several fields, including food …