Agricultural plant diseases identification: From traditional approach to deep learning

J Kotwal, R Kashyap, S Pathan - Materials Today: Proceedings, 2023 - Elsevier
Plant disease computerization in agriculture areas an important for every country, as the
population rate increases the demand for food supply also increases. Today, the significant …

A review of deep learning based anomaly detection strategies in Industry 4.0 focused on application fields, sensing equipment and algorithms

A Liso, A Cardellicchio, C Patruno, M Nitti… - IEEE …, 2024 - ieeexplore.ieee.org
Anomaly detection is a topic of interest in several areas, ranging from Industry 4.0 to Energy
Management, Smart Agriculture, Cybersecurity, and Bioinformatics. In a wide sense …

[HTML][HTML] Transformative Role of Artificial Intelligence in Advancing Sustainable Tomato (Solanum lycopersicum) Disease Management for Global Food Security: A …

B Sundararaman, S Jagdev, N Khatri - Sustainability, 2023 - mdpi.com
The growing global population and accompanying increase in food demand has put
pressure on agriculture to produce higher yields in the face of numerous challenges …

Spot-out fruit fly algorithm with simulated annealing optimized SVM for detecting tomato plant diseases

E Gangadevi, RS Rani, RK Dhanaraj… - Neural Computing and …, 2024 - Springer
Crop diseases are a huge threat to food security, yet timely detection is a difficult task due to
the absence of infrastructure in various regions of the world. In agriculture, the detection of …

[HTML][HTML] Innovative deep learning approach for cross-crop plant disease detection: A generalized method for identifying unhealthy leaves

I Bouacida, B Farou, L Djakhdjakha, H Seridi… - Information Processing …, 2024 - Elsevier
One of the most serious threats to global food security is plant diseases compromising
agricultural productivity and threatening the livelihoods of millions. These diseases can …

PlantDet: A robust multi-model ensemble method based on deep learning for plant disease detection

MSH Shovon, SJ Mozumder, OK Pal, MF Mridha… - IEEE …, 2023 - ieeexplore.ieee.org
Plant disease is a significant health concern among all living creatures. Early diagnosis can
help farmers take necessary steps to cure the disease and accelerate the production rate …

[HTML][HTML] LeafSpotNet: A deep learning framework for detecting leaf spot disease in jasmine plants

V Shwetha, A Bhagwat, V Laxmi - Artificial Intelligence in Agriculture, 2024 - Elsevier
Leaf blight spot disease, caused by bacteria and fungi, poses a threat to plant health,
leading to leaf discoloration and diminished agricultural yield. In response, we present a …

An improved deep learning approach for localization and recognition of plant leaf diseases

Y Alqahtani, M Nawaz, T Nazir, A Javed, F Jeribi… - Expert Systems with …, 2023 - Elsevier
A nation's economic progress is significantly influenced by its percentage of crop yields.
However, the major barrier to the quantity and quality of yield is crop disease. For quick and …

“Tomato-Village”: a dataset for end-to-end tomato disease detection in a real-world environment

M Gehlot, RK Saxena, GC Gandhi - Multimedia Systems, 2023 - Springer
Tomato is one of the most extensively grown vegetables in any country, and their diseases
can significantly affect yield and quality. Accurate and early detection of tomato diseases is …

Bayesian optimized multimodal deep hybrid learning approach for tomato leaf disease classification

B Khan, S Das, NS Fahim, S Banerjee, S Khan… - Scientific Reports, 2024 - nature.com
Manual identification of tomato leaf diseases is a time-consuming and laborious process that
may lead to inaccurate results without professional assistance. Therefore, an automated …