ArticlePeerJ. Computer science2021
Detecting cassava mosaic disease using a deep residual convolutional neural network with distinct block processing.
Article in PeerJ. Computer science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
- Multi-kernel inception-enhanced vision transformer for plant leaf disease recognition.Scientific reports · 2025Article
- An explainable hybrid feature aggregation network with residual inception positional encoding attention and EfficientNet for cassava leaf disease classification.Scientific reports · 2025Article
- Cassava disease detection using a lightweight modified soft attention network.Pest management science · 2025Article
- Origin-destination prediction from road average speed data using GraphResLSTM model.PeerJ. Computer science · 2025Article
- Pseudo high-frequency boosts the generalization of a convolutional neural network for cassava disease detection.Plant methods · 2022Article
- Tomato Leaf Disease Recognition on Leaf Images Based on Fine-Tuned Residual Neural Networks.Plants (Basel, Switzerland) · 2022Article
- Recognition of Leaf Disease Using Hybrid Convolutional Neural Network by Applying Feature Reduction.Sensors (Basel, Switzerland) · 2022Article
- Machine learning for optimizing daily COVID-19 vaccine dissemination to combat the pandemic.Health and technology · 2022Article
- Improved AlexNet with Inception-V4 for Plant Disease Diagnosis.Computational intelligence and neuroscience · 2022Article
- A Performance Comparison of Classification Algorithms for Rose Plants.Computational intelligence and neuroscience · 2022Article
- Classification of Plant Leaves Using New Compact Convolutional Neural Network Models.Plants (Basel, Switzerland) · 2021Article
- Dilated Semantic Segmentation for Breast Ultrasonic Lesion Detection Using Parallel Feature Fusion.Diagnostics (Basel, Switzerland) · 2021Article
- AI-Driven Framework for Recognition of Guava Plant Diseases through Machine Learning from DSLR Camera Sensor Based High Resolution Imagery.Sensors (Basel, Switzerland) · 2021Article
- A novel method for credit scoring based on feature transformation and ensemble model.PeerJ. Computer science · 2021Article
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Authors and funding
4 authors.
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Abstract
For people in developing countries, cassava is a major source of calories and carbohydrates. However, Cassava Mosaic Disease (CMD) has become a major cause of concern among farmers in sub-Saharan Africa countries, which rely on cassava for both business and local consumption. The article proposes a novel deep residual convolution neural network (DRNN) for CMD detection in cassava leaf images. With the aid of distinct block processing, we can counterbalance the imbalanced image dataset of the cassava diseases and increase the number of images available for training and testing. Moreover, we adjust low contrast using Gamma correction and decorrelation stretching to enhance the color separation of an image with significant band-to-band correlation. Experimental results demonstrate that using a balanced dataset of images increases the accuracy of classification. The proposed DRNN model outperforms the plain convolutional neural network (PCNN) by a significant margin of 9.25% on the Cassava Disease Dataset from Kaggle.
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