[HTML][HTML] An interpretable fusion model integrating lightweight CNN and transformer architectures for rice leaf disease identification
Swift identification of leaf diseases is crucial for sustainable rice farming, a staple grain
consumed globally. The high costs and inefficiencies of manual identification underline the …
consumed globally. The high costs and inefficiencies of manual identification underline the …
[HTML][HTML] Crops Disease Detection, from Leaves to Field: What We Can Expect from Artificial Intelligence
Y Lebrini, A Ayerdi Gotor - Agronomy, 2024 - mdpi.com
Agriculture is dealing with numerous challenges of increasing production while decreasing
the amount of chemicals and fertilizers used. The intensification of agricultural systems has …
the amount of chemicals and fertilizers used. The intensification of agricultural systems has …
Plant Disease Recognition: A Comprehensive Mini Review
Across the globe, agricultural yield faces numerous challenges, including unpredictable
weather patterns, resource constraints, and the ever-present threat of plant diseases. Early …
weather patterns, resource constraints, and the ever-present threat of plant diseases. Early …
Hybrid Architecture for Crop Detection and Leaf Disease Detection with Improved U-Net segmentation Model and Image Processing
P Chavan, PP Chavan, A Chavan - Crop Protection, 2025 - Elsevier
Agriculture stands as a cornerstone of India's economy, supporting the livelihoods of millions
and feeding a vast population. Enhancing crop production is imperative, given the …
and feeding a vast population. Enhancing crop production is imperative, given the …
EEG emotion recognition approach using multi-scale convolution and feature fusion
Y Zhang, Q Shan, W Chen, W Liu - The Visual Computer, 2024 - Springer
Electroencephalogram (EEG) signal has been widely applied in emotion recognition due to
its objectivity and reflection of an individual's actual emotional state. However, current EEG …
its objectivity and reflection of an individual's actual emotional state. However, current EEG …
A Comprehensive Survey on Phytopathogen Surveillance with Modern Artificial Intelligence Practices
G Kaleeswari, R Sundarrajan - 2024 International Conference …, 2024 - ieeexplore.ieee.org
The most important aspect of modern agriculture is the detection of plant diseases with the
goal of improving crop quality and output. This survey paper investigates modern …
goal of improving crop quality and output. This survey paper investigates modern …
Enhancing Precision in Rice Leaf Disease Detection: A Transformer Model Approach with Attention Mapping
Advancements in image recognition technology have significantly impacted agricultural
practices, especially in early detection of rice leaf diseases, which is crucial for maintaining …
practices, especially in early detection of rice leaf diseases, which is crucial for maintaining …
Ontology-Enhanced Disease Detection and Crop Yield Prediction in Agriculture Using ViT
The agricultural sector is evolving through data-driven precision agriculture, with a focus on
increasing plant disease detection and yield prediction. To address these issues, this study …
increasing plant disease detection and yield prediction. To address these issues, this study …
Comparative Investigation of Deep Convolutional Networks in Detection of Plant Diseases
Preserving plant health and early detection of diseases are crucial in modern agriculture.
Artificial intelligence techniques, particularly deep learning networks, are employed for this …
Artificial intelligence techniques, particularly deep learning networks, are employed for this …
A Comprehensive Analysis of Various Deep Learning Based Multi Class Plant Disease Classification Techniques
In modern agriculture, deep learning has become increasingly essential to identify plant
diseases in the field of plant disease identification with leaf images, where convolutional …
diseases in the field of plant disease identification with leaf images, where convolutional …