ArticleData in brief2023
MangoLeafBD: A comprehensive image dataset to classify diseased and healthy mango leaves.
Article in Data in brief, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 93 citations in OpenAlex.
- SAR-MLD1-2025-MangoLeaf: A comprehensive high-quality mango leaf dataset for disease classification.Data in brief · 2026Article
- Hybrid IGWO-Dingo optimized DeMoHybridNet model for multi-class leaf disease identification.Scientific reports · 2026Article
- Hybrid metaheuristic optimization of a DeepFusionNet for plant leaf disease diagnosis and recommendation.Plant methods · 2026Article
- OpenPlant: A Large-Scale Benchmark Dataset for Agricultural Plant Classification Using CNNs, ViTs, and VLMs.Plants (Basel, Switzerland) · 2026Article
- Article
- Image dataset of ten durian diseases captured in real-field conditions from a family orchard in Vinh Long, Vietnam.Data in brief · 2025Article
- Comprehensive data of 10 fruit leaf classes captured for agricultural AI applications.Data in brief · 2025Article
- Smartphone image dataset for machine learning-based monitoring and analysis of mango growth stages.Data in brief · 2025Article
- PaddyVarietyBD: Classifying paddy variations of Bangladesh with a novel image dataset.Data in brief · 2025Article
- TFP-BD: An image dataset for Traffic Flow and Pedestrian movement analysis on Bangladeshi urban roads.Data in brief · 2025Article
- Proteomics analysis revealed the activation and suppression of different host defense components challenged with mango leaf spot pathogen Alternaria alternata.BMC plant biology · 2025Article
- Enhancing anomaly detection in plant disease recognition with knowledge ensemble.Frontiers in plant science · 2025Article
- Article
- A comprehensive dataset of rice field weed detection from Bangladesh.Data in brief · 2024Article
- FruitSeg30_Segmentation dataset & mask annotations: A novel dataset for diverse fruit segmentation and classification.Data in brief · 2024Article
- Deep learning for mango leaf disease identification: A vision transformer perspective.Heliyon · 2024Article
- The impact of fine-tuning paradigms on unknown plant diseases recognition.Scientific reports · 2024Article
- A comprehensive standardized dataset of numerous pomegranate fruit diseases for deep learning.Data in brief · 2024Article
- MangoLeafBD: A comprehensive image dataset to classify diseased and healthy mango leaves.Data in brief · 2023Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Agriculture is one of the few remaining sectors that is yet to receive proper attention from the machine learning community. The importance of datasets in the machine learning discipline cannot be overemphasized. The lack of standard and publicly available datasets related to agriculture impedes practitioners of this discipline to harness the full benefit of these powerful computational predictive tools and techniques. To improve this scenario, we develop, to the best of our knowledge, the first-ever standard, ready-to-use, and publicly available dataset of mango leaves. The images are collected from four mango orchards of Bangladesh, one of the top mango-growing countries of the world. The dataset contains 4000 images of about 1800 distinct leaves covering seven diseases. Although the dataset is developed using mango leaves of Bangladesh only, since we deal with diseases that are common across many countries, this dataset is likely to be applicable to identify mango diseases in other countries as well, thereby boosting mango yield. This dataset is expected to draw wide attention from machine learning researchers and practitioners in the field of automated agriculture.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.