Related papers: An Efficient Transfer Learning-based Approach for …
While deep learning has significantly advanced automatic plant disease detection through image-based classification, improving model explainability remains crucial for reliable disease detection. In this study, we apply the Automated…
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…
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…
Mango is an important fruit crop in South Asia, but its cultivation is frequently hampered by leaf diseases that greatly impact yield and quality. This research examines the performance of five pre-trained convolutional neural networks,…
Recently, Machine Learning (ML) methods are built-in as an important component in many smart agriculture platforms. In this paper, we explore the new combination of advanced ML methods for creating a smart agriculture platform where farmers…
Automatic tomato disease recognition from leaf images is vital to avoid crop losses by applying control measures on time. Even though recent deep learning-based tomato disease recognition methods with classical training procedures showed…
Diseases in plants cause significant danger to productive and secure agriculture. Plant diseases can be detected early and accurately, reducing crop losses and pesticide use. Traditional methods of plant disease identification, on the other…
We present a transfer learning approach using a self-supervised Vision Transformer (DINOv2) for the PlantCLEF 2024 competition, focusing on the multi-label plant species classification. Our method leverages both base and fine-tuned DINOv2…
Agriculture plays an important role in the food and economy of Bangladesh. The rapid growth of population over the years also has increased the demand for food production. One of the major reasons behind low crop production is numerous…
For applications like plant disease detection, usually, a model is trained on publicly available data and tested on field data. This means that the test data distribution is not the same as the training data distribution, which affects the…
Pumpkin leaf diseases are significant threats to agricultural productivity, requiring a timely and precise diagnosis for effective management. Traditional identification methods are laborious and susceptible to human error, emphasizing the…
This study evaluates the efficacy of three deep learning architectures: ResNet50, MobileNetV2, and EfficientNetB0 for automated plant species classification based on leaf venation patterns, a critical morphological feature with high…
The purpose of the Insect Detection System for Crop and Plant Health is to keep an eye out for and identify insect infestations in farming areas. By utilizing cutting-edge technology like computer vision and machine learning, the system…
Plant diseases are a major threat to food security globally. It is important to develop early detection systems which can accurately detect. The advancement in computer vision techniques has the potential to solve this challenge. We have…
Modern scientific and technological advances allow botanists to use computer vision-based approaches for plant identification tasks. These approaches have their own challenges. Leaf classification is a computer-vision task performed for the…
Plant diseases significantly impact our food supply, causing problems for farmers, economies reliant on agriculture, and global food security. Accurate and timely plant disease diagnosis is crucial for effective treatment and minimizing…
Plant diseases are the primary cause of crop losses globally, with an impact on the world economy. To deal with these issues, smart agriculture solutions are evolving that combine the Internet of Things and machine learning for early…
Apple orchards require timely disease detection, fruit quality assessment, and yield estimation, yet existing UAV-based systems address such tasks in isolation and often rely on costly multispectral sensors. This paper presents a unified,…
Plant diseases serve as one of main threats to food security and crop production. It is thus valuable to exploit recent advances of artificial intelligence to assist plant disease diagnosis. One popular approach is to transform this problem…
Agriculture is the mainstay of human society because it is an essential need for every organism. Paddy cultivation is very significant so far as humans are concerned, largely in the Asian continent, and it is one of the staple foods.…