相关论文: Deep Learning-Based Computational Model for Diseas…
Plant disease detection is a huge problem and often require professional help to detect the disease. This research focuses on creating a deep learning model that detects the type of disease that affected the plant from the images of the…
A very crucial part of Bangladeshi people's employment, GDP contribution, and mainly livelihood is agriculture. It plays a vital role in decreasing poverty and ensuring food security. Plant diseases are a serious stumbling block in…
Agriculture is an essential industry in the both society and economy of a country. However, the pests and diseases cause a great amount of reduction in agricultural production while there is not sufficient guidance for farmers to avoid this…
Addressing plant diseases and pests is critical for enhancing crop production and preventing economic losses. Recent advances in artificial intelligence (AI), machine learning (ML), and deep learning (DL) have significantly improved the…
This work presents a deep learning-based plant disease diagnostic system using images of fruits and leaves. Five state-of-the-art convolutional neural networks (CNN) have been employed for implementing the system. Hitherto model accuracy…
Pests and diseases pose a key challenge to passion fruit farmers across Uganda and East Africa in general. They lead to loss of investment as yields reduce and losses increases. As the majority of the farmers, including passion fruit…
Plant diseases are considered one of the main factors influencing food production and minimize losses in production, and it is essential that crop diseases have fast detection and recognition. The recent expansion of deep learning methods…
In Bangladesh, tomatoes are a staple vegetable, prized for their versatility in various culinary applications. However, the cultivation of tomatoes is often hindered by a range of diseases that can significantly reduce crop yields and…
A new method of recognizing apple leaf diseases through region-of-interest-aware deep convolutional neural network is proposed in this paper. The primary idea is that leaf disease symptoms appear in the leaf area whereas the background…
To ensure global food security and the overall profit of stakeholders, the importance of correctly detecting and classifying plant diseases is paramount. In this connection, the emergence of deep learning-based image classification has…
We have developed a comprehensive computer system to assist farmers who practice traditional farming methods and have limited access to agricultural experts for addressing crop diseases. Our system utilizes artificial intelligence (AI) to…
An accurate and timely detection of diseases and pests in rice plants can help farmers in applying timely treatment on the plants and thereby can reduce the economic losses substantially. Recent developments in deep learning based…
Global Coconut (Cocos nucifera (L.)) cultivation faces significant challenges, including yield loss, due to pest and disease outbreaks. In particular, Weligama Coconut Leaf Wilt Disease (WCWLD) and Coconut Caterpillar Infestation (CCI)…
Smallholder farmers in Tanzania are challenged on the lack of tools for early detection of banana diseases. This study aimed at developing a mobile application for early detection of Fusarium wilt race 1 and black Sigatoka banana diseases…
Mango cultivation is crucial in the agricultural sector, significantly contributing to economic development and food security. However, diseases affecting mango leaves can significantly reduce both the production and overall fruit grade.…
Plant diseases significantly impact agricultural productivity, resulting in economic losses and food insecurity. Prompt and accurate detection is crucial for the efficient management and mitigation of plant diseases. This study investigates…
Tea leaf diseases are a major challenge to agricultural productivity, with far-reaching implications for yield and quality in the tea industry. The rise of machine learning has enabled the development of innovative approaches to combat…
Timely and rapid diagnoses are core to informing on optimum interventions that curb the spread of COVID-19. The use of medical images such as chest X-rays and CTs has been advocated to supplement the Reverse-Transcription Polymerase Chain…
Sweet orange leaf diseases are significant to agricultural productivity. Leaf diseases impact fruit quality in the citrus industry. The apparition of machine learning makes the development of disease finder. Early detection and diagnosis…
Plant diseases pose a serious challenge to agriculture by reducing crop yield and affecting food quality. Early detection and classification of these diseases are essential for minimising losses and improving crop management practices. This…