Mango Diseases Classification Solutions Using Machine Learning or Deep Learning: A Review

Faye, Demba; Diop, Idy; Dione, Doudou

doi:10.4236/jcc.2022.1012002

Cited by 11 publications

(5 citation statements)

References 21 publications

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“…Idy Diop [16], has contributed to a review study in which the author concentrates on the CNN algorithm. Mango leaf and fruit are included in the dataset.…”

Section: Literature Surveymentioning

confidence: 99%

Classification of Mango Leaf Disease using Machine Learning to Enhance Yield Productivity

Harshali Patil, Varsha Bendre, Jayashree Katti

2024

jes

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Fruits provide critical nourishment to the human body. Proper Care and upkeep are essential for the fruit to be healthy. Lack of maintenance, infections, spot, fungus all cause significant production and profit losses. Mango is a seasonal and famous fruit which is consumed all over the world. It is a delicate fruit that is susceptible to disease that reduce the quality as well as quantity. Manual illness or infection inspection is a time-consuming and labour-intensive technique that necessitates a large amount of resources and therefore it is inefficient. On the other hand, automatic inspection provides various advantages such as less time consuming, less labour and also the number of resources required are less. Image classification techniques and algorithms can be used to distinguish between infected and healthy mangoes, decreasing losses.

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“…Idy Diop [16], has contributed to a review study in which the author concentrates on the CNN algorithm. Mango leaf and fruit are included in the dataset.…”

Section: Literature Surveymentioning

confidence: 99%

Classification of Mango Leaf Disease using Machine Learning to Enhance Yield Productivity

Harshali Patil, Varsha Bendre, Jayashree Katti

2024

jes

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“…Over the past decade, the push towards automating mango disease diagnosis has grown, utilizing ML (Machine Learning) and DL (Deep Learning) solutions. This literature [28] categorized these results into two: those built on traditional ML algorithms and those rooted in DL. Notably, the Convolutional Neural Network (CNN), a form of DL, has garnered widespread attention for its exceptional performance in recent years.…”

Section: Literature Surveymentioning

confidence: 99%

MDCN: Modified Dense Convolution Network Based Disease Classification in Mango Leaves

Chandrashekar,

Vijayakumar,

Pradeep

et al. 2024

CMC

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The most widely farmed fruit in the world is mango. Both the production and quality of the mangoes are hampered by many diseases. These diseases need to be effectively controlled and mitigated. Therefore, a quick and accurate diagnosis of the disorders is essential. Deep convolutional neural networks, renowned for their independence in feature extraction, have established their value in numerous detection and classification tasks. However, it requires large training datasets and several parameters that need careful adjustment. The proposed Modified Dense Convolutional Network (MDCN) provides a successful classification scheme for plant diseases affecting mango leaves. This model employs the strength of pre-trained networks and modifies them for the particular context of mango leaf diseases by incorporating transfer learning techniques. The data loader also builds mini-batches for training the models to reduce training time. Finally, optimization approaches help increase the overall model's efficiency and lower computing costs. MDCN employed on the MangoLeafBD Dataset consists of a total of 4,000 images. Following the experimental results, the proposed system is compared with existing techniques and it is clear that the proposed algorithm surpasses the existing algorithms by achieving high performance and overall throughput.

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“…Demba Faye [16] has worked on a review paper and the author focuses on CNN algorithm. The dataset consists of Mango leaf, fruit.…”

Section: Sarder Iftekhar Ahmedmentioning

confidence: 99%

Automatic Classification of Mango Leaf Disease based on Machine Learning and Deep Learning Techniques

Deepali Joshi

2023

IJRITCC

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Fruits are the essential source of nutrition for the human body. The fruit needs to be nurtured and cared for in order to remain healthy. Lack of upkeep, illnesses, blemishes, and fungi result in a considerable loss of produce and profit. One of the important and popular fruit that is consumed worldwide is Mango. It is a fragile fruit and is vulnerable to diseases that affects its quality and quantity. Manual inspection for diseases or infection is a tedious process and requires abundant resources such as time and labour. Manual inspection is inefficient and inaccurate. Automatic inspection on the other hand has numerous benefits. The image classification techniques and algorithms can be used to detect infected and healthy mangoes thus reducing the losses to the farmers.

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Mango Diseases Classification Solutions Using Machine Learning or Deep Learning: A Review

Cited by 11 publications

References 21 publications

Classification of Mango Leaf Disease using Machine Learning to Enhance Yield Productivity

Classification of Mango Leaf Disease using Machine Learning to Enhance Yield Productivity

MDCN: Modified Dense Convolution Network Based Disease Classification in Mango Leaves

Automatic Classification of Mango Leaf Disease based on Machine Learning and Deep Learning Techniques

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