A systematic review of deep learning techniques for plant diseases
Agriculture is one of the most crucial sectors, meeting the fundamental food needs of
humanity. Plant diseases increase food economic and food security concerns for countries …
humanity. Plant diseases increase food economic and food security concerns for countries …
Detecting refactoring type of software commit messages based on ensemble machine learning algorithms
Refactoring is a well-established topic in contemporary software engineering, focusing on
enhancing software's structural design without altering its external behavior. Commit …
enhancing software's structural design without altering its external behavior. Commit …
Optimized transfer learning approach for leaf disease classification in smart agriculture
In recent years, numerous deep learning architectures have used publicly available/author-
generated datasets to classify plant diseases. This study suggested a four-stage process for …
generated datasets to classify plant diseases. This study suggested a four-stage process for …
Local and global feature-aware dual-branch networks for plant disease recognition
Accurate identification of plant diseases is important for ensuring the safety of agricultural
production. Convolutional neural networks (CNNs) and visual transformers (VTs) can extract …
production. Convolutional neural networks (CNNs) and visual transformers (VTs) can extract …
MultiFuseYOLO: Redefining Wine Grape Variety Recognition through Multisource Information Fusion
J Peng, C Ouyang, H Peng, W Hu, Y Wang, P Jiang - Sensors, 2024 - mdpi.com
Based on the current research on the wine grape variety recognition task, it has been found
that traditional deep learning models relying only on a single feature (eg, fruit or leaf) for …
that traditional deep learning models relying only on a single feature (eg, fruit or leaf) for …
IDBNWP: improved deep belief network for workload prediction: hybrid optimization for load balancing in cloud system
The achievement of cloud environment is determined by the efficiency of its load balancing
with proper allocation of resources. The proactive forecasting of future workload …
with proper allocation of resources. The proactive forecasting of future workload …
[PDF][PDF] A wavelet CNN with appropriate feed-allocation and PSO optimized activations for diabetic retinopathy grading
This work modifies the architecture of conventional CNN with the integration of Multi-
resolution Analysis (MRA) in a CNN framework for Diabetic Retinopathy (DR) diagnosis and …
resolution Analysis (MRA) in a CNN framework for Diabetic Retinopathy (DR) diagnosis and …
Development of a handheld GPU-assisted DSC-TransNet model for the real-time classification of plant leaf disease using deep learning approach
In agriculture, promptly and accurately identifying leaf diseases is crucial for sustainable
crop production. To address this requirement, this research introduces a hybrid deep …
crop production. To address this requirement, this research introduces a hybrid deep …
A hybrid deep learning neural network for early plant disease diagnosis using a real-world Wheat–Barley vision dataset: challenges and solutions
Approximately 35% of India's annual crop yield is lost due to plant diseases. Due to a lack of
lab equipment and infrastructure, early diagnosis of plant diseases remains challenging …
lab equipment and infrastructure, early diagnosis of plant diseases remains challenging …
KEXNet: A Knowledge-Enhanced Model for Improved Chest X-Ray Lesion Detection
Automated diagnosis of chest X-rays is pivotal in radiology, aiming to alleviate the workload
of radiologists. Traditional methods primarily rely on visual features or label dependence …
of radiologists. Traditional methods primarily rely on visual features or label dependence …