On using artificial intelligence and the internet of things for crop disease detection: A contemporary survey
The agricultural sector remains a key contributor to the Moroccan economy, representing
about 15% of gross domestic product (GDP). Disease attacks are constant threats to …
about 15% of gross domestic product (GDP). Disease attacks are constant threats to …
A novel multi-head CNN design to identify plant diseases using the fusion of RGB images
Plant diseases and insect pests cause a significant threat to agricultural production. Early
detection and diagnosis of these diseases are critical and can reduce economic losses. The …
detection and diagnosis of these diseases are critical and can reduce economic losses. The …
Crop-saving with AI: latest trends in deep learning techniques for plant pathology
Plant diseases pose a major threat to agricultural production and the food supply chain, as
they expose plants to potentially disruptive pathogens that can affect the lives of those who …
they expose plants to potentially disruptive pathogens that can affect the lives of those who …
FieldPlant: A dataset of field plant images for plant disease detection and classification with deep learning
E Moupojou, A Tagne, F Retraint, A Tadonkemwa… - IEEE …, 2023 - ieeexplore.ieee.org
The Food and Agriculture Organization of the United Nations suggests increasing the food
supply by 70% to feed the world population by 2050, although approximately one third of all …
supply by 70% to feed the world population by 2050, although approximately one third of all …
Systematic study on deep learning-based plant disease detection or classification
Plant diseases impact extensively on agricultural production growth. It results in a price hike
on food grains and vegetables. To reduce economic loss and to predict yield loss, early …
on food grains and vegetables. To reduce economic loss and to predict yield loss, early …
Hybrid Model to Predict Leaf Disease Prediction Using Ensembling Machine Learning Approach
G Endait, A Nikam, P Bhorkade… - … on Communication & …, 2023 - ieeexplore.ieee.org
In this work, the use of machine learning to forecast instances of leaf disease is advocated.
The automated leaf disease detection system used in precision agriculture makes use of …
The automated leaf disease detection system used in precision agriculture makes use of …
Enhancing sugarcane disease classification with ensemble deep learning: A comparative study with transfer learning techniques
Deep learning practices in the agriculture sector can address many challenges faced by the
farmers such as disease detection, yield estimation, soil profile estimation, etc. In this paper …
farmers such as disease detection, yield estimation, soil profile estimation, etc. In this paper …
Image segmentation method for sweetgum leaf spots based on an improved DeeplabV3+ network
This paper discusses a sweetgum leaf-spot image segmentation method based on an
improved DeeplabV3+ network to address the low accuracy in plant leaf spot segmentation …
improved DeeplabV3+ network to address the low accuracy in plant leaf spot segmentation …
Harnessing the power of diffusion models for plant disease image augmentation
Introduction The challenges associated with data availability, class imbalance, and the need
for data augmentation are well-recognized in the field of plant disease detection. The …
for data augmentation are well-recognized in the field of plant disease detection. The …
Enhanced segmentation with optimized nine-layered CNN-based classification of leaf diseases: an automatic approach for plant disease diagnosis
P Chillakuru, D Divya, K Ananthajothi - cybernetics and systems, 2024 - Taylor & Francis
The task of monitoring the plant leaves is considered to be error-prone, inconsistent, and
unreliable. Thus, certain deep learning algorithms are developed to detect plant leaf …
unreliable. Thus, certain deep learning algorithms are developed to detect plant leaf …