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Agricultural plant diseases identification: From traditional approach to deep learning
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 …
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
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 …
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 …
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 …
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
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 …
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
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 …
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
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 …
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
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 …
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
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 …
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
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 …
may lead to inaccurate results without professional assistance. Therefore, an automated …