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Enhancing Land Use Identification Through Fusion of Densenet121 DCNN and Thepade SBTC Features Using Machine Learning Algorithms and Ensembles
Aerial vehicles such as drones are used to capture high-resolution images are also called aerial images. Using these aerial images for the...
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Coffee Leaf Disease Classification by Using a Hybrid Deep Convolution Neural Network
The most common symptoms of coffee leaf disease are coffee leaf rust, black rot diseases, and brown eye spot. Leaf rust is the first symptom of...
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A deep learning-based approach for the identification of selected species of genus Euphorbia L.
The classification of Euphorbia species is a challenging task due to their diverse growth forms and morphological features. In this paper, we have...
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Grapevine fruits disease detection using different deep learning models
In India, grapes are one of the most important crops for business. Grapes and their byproducts are one of India’s leading exports. The leaves of...
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Machine learning methods for the industrial robotic systems security
The trends in the introduction of industrial and logistics robots into the social sphere of activity in order to ensure the safety of civilian...
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Eye diseases diagnosis using deep learning and multimodal medical eye imaging
The present study carries out an empirical evaluation and comparison of the seven most recent deep Convolutional Neural Network (CNN) techniques...
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A deep learning approach for early detection of drought stress in maize using proximal scale digital images
Neural computing methods pose an edge over conventional methods for drought stress identification because of their ease of implementation, accuracy,...
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Plant leaf disease detection and classification using modified transfer learning models
Agriculture is a dominating field that plays an essential role in the economic development of any country. In India, agriculture contributes about...
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JUIVCDv1: development of a still-image based dataset for indian vehicle classification
An automatic vehicle classification (AVC) system designed from either still images or videos has the potential to bring significant benefits to the...
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AI-based smart agriculture 4.0 system for plant diseases detection in Tunisia
Plant diseases pose a significant problem for agricultural sustainability, notably reducing crop quality and yield. Addressing this challenge, this...
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Snake species classification using deep learning techniques
Incorrect snake identification from the observable visual traits is a major reason of death resulting from snake bites. The classification of snake...
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A novel lightweight CNN for chest X-ray-based lung disease identification on heterogeneous embedded system
The global spread of epidemic lung diseases, including COVID-19, underscores the need for efficient diagnostic methods. Addressing this, we developed...
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Stroke detection in the brain using MRI and deep learning models
When it comes to finding solutions to issues, deep learning models are pretty much everywhere. Medical image data is best analysed using models based...
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Automated Seed Classification Using State-of-the-Art Techniques
The demand for efficient and accurate seed assessment is paramount in modern agriculture to ensure good crop yield. This work presents a system for...
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Automatic mango leaf disease detection using different transfer learning models
The cultivation of mangoes contributes significantly to the economy and food security of many tropical and subtropical regions. However, mango trees...
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Intelligent waste classification approach based on improved multi-layered convolutional neural network
This study aims to improve the performance of organic to recyclable waste through deep learning techniques. Negative impacts on environmental and...
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Edge preserved universal pooling: novel strategies for pooling in convolutional neural networks
Anti-aliased Convolutional Neural Networks (CNNs) have been proposed to overcome the shift variant nature of the CNNs. The fundamental building block...
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Breast lesions segmentation and classification in a two-stage process based on Mask-RCNN and Transfer Learning
The most prevalent malignancy of concern among women is breast cancer. Early detection plays a crucial role in improving survival chances. However,...
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An automated deep learning models for classification of skin disease using Dermoscopy images: a comprehensive study
With the explosion of advanced Information and Recognition model, primarily the Deep Learning (DL) and Transfer Learning (TL) models, all aspects of...
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Classifying diabetic macular edema grades using extended power of deep learning
Diabetic macular edema (DME) is the expansion of the disease diabetic retinopathy (DR). Diabetic persons with a severe risk of DME can enter the...
