Research graph
References from MultiNet: A lightweight deep learning group of models for fruit maturity detection. Local targets link to admitted publications; unresolved targets remain external evidence.
PND-Net: physics-inspired non-local dual-domain network for metal artifact reduction
10.1109/tmi.2024.3354925 · 2024 · External reference
Tomato maturity recognition with convolutional transformers
10.1038/s41598-023-50129-w · 2023 · External reference
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Deep residual learning for image recognition
2016 · External reference
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A novel dataset of guava fruit for grading and classification
10.1016/j.dib.2023.109462 · 2023 · External reference
A novel dataset of date fruit for inspection and classification
10.1016/j.dib.2023.110026 · 2024 · External reference
A dataset of pomegranate growth stages for machine learning-based monitoring and analysis
10.1016/j.dib.2023.109468 · 2023 · External reference
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Classification of cocoa pod maturity using similarity tools on an image database: comparison of feature extractors and color spaces
10.3390/data8060099 · 2023 · External reference
RipSetCocoaCNCH12: Labeled Dataset for Ripeness Stage Detection, Semantic and Instance Segmentation of Cocoa Pods
10.3390/data8060112 · 2023 · External reference
A Deep Learning-Based Model for Date Fruit Classification
10.3390/su14106339 · 2022 · External reference
Evaluation of convolutional neural networks’ hyperparameters with transfer learning to determine sorting of ripe Medjool dates
10.3390/agriculture11020115 · 2021 · External reference
FruitSeg30_Segmentation dataset & mask annotations: a novel dataset for diverse fruit segmentation and classification
10.1016/j.dib.2024.110821 · 2024 · External reference
An efficient detection of the pitaya growth status based on the YOLOv8n-CBN model
10.3390/horticulturae10090899 · 2024 · External reference
Annotated datasets of oil palm fruit bunch piles for ripeness grading using deep learning
10.1038/s41597-023-01958-x · 2023 · External reference
Oil palm fresh fruit bunch ripeness classification on mobile devices using deep learning approaches
10.1016/j.compag.2021.106359 · 2021 · External reference
Real-time oil palm ripeness classification of fresh fruit bunches using fluorescence technology
2023 · External reference
Determining quality and maturity of pomegranates using multispectral imaging
10.1016/j.jssas.2015.10.004 · 2017 · External reference
Non-destructive evaluation of maturity and quality parameters of pomegranate fruit by visible/near infrared spectroscopy
10.1080/10942912.2015.1126725 · 2017 · External reference
Tomato maturity detection and counting model based on MHSA-YOLOv8
10.3390/s23156701 · 2023 · External reference
10.1007/978-3-030-01234-2_1
10.1007/978-3-030-01234-2_1 · External reference
10.1109/cvpr42600.2020.01155
10.1109/cvpr42600.2020.01155 · External reference
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Searching for MobileNetV3
2019 · External reference
Xception: deep learning with depthwise separable convolutions
2017 · External reference
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Deep learning optimization for edge devices: analysis of training quantization parameters
2019 · External reference
