Research graph
References from AI-driven hybrid vision transformer for automated disease classification in tomato (Solanum lycopersicum L.) crop under high altitude covered cultivation. Local targets link to admitted publications; unresolved targets remain external evidence.
Artificial intelligence in tomato leaf disease detection: a comprehensive review and discussion
10.1007/s41348-021-00500-8 · 2022 · External reference
Tomato brown rugose fruit virus: a pathogen that is changing the tomato production worldwide
10.1111/aab.12788 · 2022 · External reference
A key frame extraction method for processing greenhouse vegetables production monitoring video
10.1016/j.compag.2014.12.007 · 2015 · External reference
Performance of tomato under greenhouse and open field conditions in the trans-Himalayan region of India
10.13128/ahs-12786 · 2011 · External reference
Prediction models for identification and diagnosis of tomato plant diseases
2018 · External reference
A robust deep-learning-based detector for real-time tomato plant diseases and pests recognition
10.3390/s17092022 · 2017 · External reference
Embedded system for regulating abiotic parameters for Capsicum cultivation in a polyhouse with comparison to open-field cultivation
10.1080/19315260.2019.1654588 · 2020 · External reference
Nutrient and water use efficiency of cucumbers grown in soilless media under a naturally ventilated greenhouse
2019 · External reference
Computer vision, IoT and data fusion for crop disease detection using machine learning: a survey and ongoing research
10.3390/rs13132486 · 2021 · External reference
Data augmentation for improving deep learning in image classification problem
2018 · External reference
Convolutional neural networks: an overview and application in radiology
10.1007/s13244-018-0639-9 · 2018 · External reference
Deep convolutional neural network models for weed detection in polyhouse grown bell peppers
2022 · External reference
Leaves diseases detection of tomato using image processing
2019 · External reference
Model-based statistical features for mobile phone image of tomato plant disease classification
2017 · External reference
Vision transformers for remote sensing image classification
10.3390/rs13030516 · 2021 · External reference
Vision transformer approach for classification of Alzheimer's disease using 18F-Florbetaben brain images
10.3390/app13063453 · 2023 · External reference
Unresolved reference
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CMT: convolutional neural networks meet vision transformers
2022 · External reference
Classification of Alzheimer's disease via vision transformer: classification of Alzheimer's disease via vision transformer
2022 · External reference
OViTAD: optimized vision transformer to predict various stages of Alzheimer's disease using resting-state fMRI and structural MRI data
10.3390/brainsci13020260 · 2023 · External reference
10.1016/j.ecoinf.2023.102245
10.1016/j.ecoinf.2023.102245 · External reference
SMIL-DeiT: multiple instance learning and self-supervised vision transformer network for early Alzheimer's disease classification
2022 · External reference
Unresolved reference
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Going deeper with convolutions
2015 · External reference
Deep residual learning for image recognition
2016 · External reference
Unresolved reference
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Densely connected convolutional networks
2017 · External reference
Xception: deep learning with depthwise separable convolutions
2017 · External reference
ShuffleNet: an extremely efficient convolutional neural network for mobile devices
2018 · External reference
Unresolved reference
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Identifying crop water stress using deep learning models
10.1007/s00521-020-05325-4 · 2021 · External reference
Performance comparison of multiple convolutional neural networks for concrete defects classification
10.3390/s22228714 · 2022 · External reference
Pneumonia classification from X-ray images with Inception-V3 and convolutional neural network
10.3390/diagnostics12051280 · 2022 · External reference
Detection of K-complexes in EEG waveform images using faster R-CNN and deep transfer learning
10.1186/s12911-022-02042-x · 2022 · External reference
Rethinking the inception architecture for computer vision
2016 · External reference
Conv-ViT: a convolution and vision transformer-based hybrid feature extraction method for retinal disease detection
10.3390/jimaging9070140 · 2023 · External reference
10.1109/iccv48922.2021.00009
10.1109/iccv48922.2021.00009 · External reference
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Performance modeling of a groundnut stripper using response surface methodology
2013 · External reference
Hyperparameter tuning of machine learning algorithms using response surface methodology: a case study of ANN, SVM, and DBN
10.1155/2022/8513719 · 2022 · External reference
A survey on image data augmentation for deep learning
10.1186/s40537-019-0197-0 · 2019 · External reference
End-to-end object detection with transformers
2020 · External reference
Unresolved reference
2015 · External reference
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Unresolved reference
2009 · External reference
Image classification and prediction using transfer learning in Colab notebook
10.1016/j.gltp.2021.08.068 · 2021 · External reference
Classification assessment methods
2021 · External reference
Optimisation and modelling of draft and rupture width using response surface methodology and artificial neural network for tillage tools
10.1071/sr21271 · 2022 · External reference
Enhancement of tea leaf diseases identification using modified SOTA models
10.1007/s00521-024-10758-2 · 2025 · External reference
Identification of plant leaf diseases by deep learning based on channel attention and channel pruning
2022 · External reference
Tea leaf disease detection and identification based on YOLOv7 (YOLO-T)
10.1038/s41598-023-33270-4 · 2023 · External reference
Modified MobileNet with leaky ReLU and LSTM with balancing technique to classify the soil types
10.1007/s12145-024-01521-1 · 2025 · External reference
An efficient plant disease detection using transfer learning approach
10.1038/s41598-025-02271-w · 2025 · External reference
Detection of tomato leaf diseases for agro-based industries using novel PCA DeepNet
10.1109/access.2023.3244499 · 2023 · External reference
Modified transfer learning frameworks to identify potato leaf diseases
10.1007/s11042-023-17610-0 · 2024 · External reference
Tomato disease recognition using a compact convolutional neural network
10.1109/access.2022.3192428 · 2022 · External reference
Less is more: lighter and faster deep neural architecture for tomato leaf disease classification
10.1109/access.2022.3187203 · 2022 · External reference
Intelligent plant leaf disease detection using generative adversarial networks: a case-study of Cassava leaves
10.2174/0118743315288623240223072349 · 2025 · External reference
Design of efficient methods for the detection of tomato leaf disease utilizing proposed ensemble CNN model
2023 · External reference
Plant disease detection with deep learning and feature extraction using plant village
10.4236/jcc.2020.86002 · 2020 · External reference
Leveraging AI and ML in precision farming for pest and disease management: benefits, challenges, and future prospects
2025 · External reference
Disease control measures using vision-enabled agricultural robotics
2024 · External reference
A comparative study of CNN and transformer models for image recognition
2025 · External reference
DA-TransUNet: integrating spatial and channel dual attention with transformer U-net for medical image segmentation
10.3389/fbioe.2024.1398237 · 2024 · External reference
