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Enhancing Diseases Classification in Maize and Cassava Crops Using Pre-Trained Cnn Models and Layer Thawing Strategy
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inferredcites →https://doi.org/10.1007/978-3-031-28183-9_8openalex-snapshot
Deep Learning for the Classification of Cassava Leaf Diseases in Unbalanced Field Data Set
inferredcites →https://doi.org/10.1007/978-3-319-46493-0_38openalex-snapshot
Identity Mappings in Deep Residual Networks
inferredcites →https://doi.org/10.1007/978-981-19-3148-2_21openalex-snapshot
Maize Leaf Disease Detection Using Convolutional Neural Network
inferredcites →https://doi.org/10.1007/978-981-19-8742-7_15openalex-snapshot
Cassava Leaf Disease Detection Using Ensembling of EfficientNet, SEResNeXt, ViT, DeIT and MobileNetV3 Models
inferredcites →https://doi.org/10.1007/978-981-33-4968-1_17openalex-snapshot
Capsnet-VGG16 Architecture for Cassava Plant Disease Detection
inferredcites →https://doi.org/10.1007/978-981-99-1946-8_38openalex-snapshot
A Deep Learning-Based InceptionResNet V2 Model for Cassava Leaf Disease Detection
inferredcites →https://doi.org/10.1007/978-981-99-7456-6_6openalex-snapshot
Disease Classification in Cassava Plant by Artificial Neural Network
inferredcites →https://doi.org/10.1007/s11042-022-14004-6openalex-snapshot
Intelligent plant disease diagnosis using convolutional neural network: a review
inferredcites →https://doi.org/10.1007/s42979-024-02620-yopenalex-snapshot
Lightweight Convolutional Neural Network Model for Cassava Leaf Diseases Classification
inferredcites →https://doi.org/10.1016/j.compag.2020.105527openalex-snapshot
Deep feature based rice leaf disease identification using support vector machine
inferredcites →https://doi.org/10.1016/j.ecoinf.2021.101502openalex-snapshot
Hybrid convolution neural network model for a quicker detection of infested maize plants with fall armyworms using UAV-based images
inferredcites →https://doi.org/10.1016/j.eij.2020.02.007openalex-snapshot
A predictive machine learning application in agriculture: Cassava disease detection and classification with imbalanced dataset using convolutional neural networks
inferredcites →https://doi.org/10.1016/j.imu.2023.101363openalex-snapshot
Deep feature extraction based cascading model for the classification of Fusarium stalk rot and charcoal rot disease in maize plant
inferredcites →https://doi.org/10.1016/j.inpa.2016.10.005openalex-snapshot
Detection of plant leaf diseases using image segmentation and soft computing techniques
inferredcites →https://doi.org/10.1016/j.jafr.2023.100824openalex-snapshot
Maize disease identification based on optimized support vector machine using deep feature of DenseNet201
inferredcites →https://doi.org/10.1016/j.jii.2024.100572openalex-snapshot
A review on machine learning and deep learning image-based plant disease classification for industrial farming systems
inferredcites →https://doi.org/10.1016/j.procs.2023.01.149openalex-snapshot
Convolutional Neural Network Based Maize Plant Disease Identification
inferredcites →https://doi.org/10.1016/j.virusres.2011.04.018openalex-snapshot
Comparing the regional epidemiology of the cassava mosaic and cassava brown streak virus pandemics in Africa
inferredcites →https://doi.org/10.1016/s0168-1702(00)00194-5openalex-snapshot
Cassava mosaic virus disease in East Africa: a dynamic disease in a changing environment
inferredcites →https://doi.org/10.1080/87559120500379787openalex-snapshot
Utilization Potentials of Cassava in Nigeria: The Domestic and Industrial Products
inferredcites →https://doi.org/10.1109/access.2023.3263042openalex-snapshot
FieldPlant: A Dataset of Field Plant Images for Plant Disease Detection and Classification With Deep Learning
inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-snapshot
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/cvpr.2016.308openalex-snapshot
Rethinking the Inception Architecture for Computer Vision
inferredcites →https://doi.org/10.1109/cvpr.2017.243openalex-snapshot
Densely Connected Convolutional Networks
inferredcites →https://doi.org/10.1109/iccpct58313.2023.10245357openalex-snapshot
Decentralized Detection of Cassava Leaf Diseases: A Federated Convolutional Neural Network Solution
inferredcites →https://doi.org/10.1109/iciccs56967.2023.10142559openalex-snapshot
A Study of Deep Learning based Techniques for the Detection of Maize Leaf Disease: A Short Review
inferredcites →https://doi.org/10.1109/icsec.2017.8443919openalex-snapshot
Corn Disease Identification from Leaf Images Using Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/iemtronics55184.2022.9795751openalex-snapshot
Cassava Leaf Disease Detection Using Deep Learning
inferredcites →https://doi.org/10.1109/incacct57535.2023.10141847openalex-snapshot
Maize Disease classification using Deep Learning Techniques: A Review
inferredcites →https://doi.org/10.1109/incet57972.2023.10170182openalex-snapshot
Maize Leaf Diseases Classification using a Deep Learning Algorithm
inferredcites →https://doi.org/10.1109/incet57972.2023.10170499openalex-snapshot
Revolutionizing Maize Disease Management with Federated Learning CNNs: A Decentralized and Privacy-Sensitive Approach
inferredcites →https://doi.org/10.1109/ispa59904.2024.10536790openalex-snapshot
Black rot disease classification of apples and grapes using convolutional neural network and transfer learning
inferredcites →https://doi.org/10.1111/j.1541-4337.2010.00117.xopenalex-snapshot
Maize: A Paramount Staple Crop in the Context of Global Nutrition
inferredcites →https://doi.org/10.1111/mpp.12613openalex-snapshot
Cassava brown streak disease: historical timeline, current knowledge and future prospects
inferredcites →https://doi.org/10.1609/aaai.v31i1.11231openalex-snapshot
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1511.08060openalex-snapshot
An open access repository of images on plant health to enable the development of mobile disease diagnostics
inferredcites →https://doi.org/10.48550/arxiv.1908.02900openalex-snapshot
iCassava 2019 Fine-Grained Visual Categorization Challenge
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