Recognition of leaf disease using hybrid convolutional neural network by applying feature reduction
Agriculture is crucial to the economic prosperity and development of India. Plant diseases
can have a devastating influence towards food safety and a considerable loss in the …
can have a devastating influence towards food safety and a considerable loss in the …
Multimodal brain tumor detection and classification using deep saliency map and improved dragonfly optimization algorithm
In the last decade, there has been a significant increase in medical cases involving brain
tumors. Brain tumor is the tenth most common type of tumor, affecting millions of people …
tumors. Brain tumor is the tenth most common type of tumor, affecting millions of people …
Weed density estimation in soya bean crop using deep convolutional neural networks in smart agriculture
Weeds are those unwanted plants that grow between cultivated crops, which reduce the
purity of the crops. Crops are severely affected by weeds for their quality and yields. Farmers …
purity of the crops. Crops are severely affected by weeds for their quality and yields. Farmers …
Deep learning implementation of image segmentation in agricultural applications: a comprehensive review
L Lei, Q Yang, L Yang, T Shen, R Wang… - Artificial Intelligence …, 2024 - Springer
Image segmentation is a crucial task in computer vision, which divides a digital image into
multiple segments and objects. In agriculture, image segmentation is extensively used for …
multiple segments and objects. In agriculture, image segmentation is extensively used for …
A method noise-based convolutional neural network technique for CT image Denoising
Medical imaging is a complex process that capitulates images created by X-rays, ultrasound
imaging, angiography, etc. During the imaging process, it also captures image noise during …
imaging, angiography, etc. During the imaging process, it also captures image noise during …
Neural Networks for the Diagnosis of Covid-19 in Chest X-ray Images: A Systematic Review and Meta-Analysis
DC Andrade-Girón, WJ Marín-Rodriguez… - … on Pervasive Health …, 2023 - eudl.eu
Introduction: The COVID-19 pandemic has triggered a global crisis with significant
repercussions in terms of mortality and an ever-increasing demand for urgent medical care …
repercussions in terms of mortality and an ever-increasing demand for urgent medical care …
Comparative approach for early diabetes detection with machine learning
The detrimental effects of diabetes are currently affecting a sizeable section of the
population worldwide, and many of these individuals are not being properly diagnosed. This …
population worldwide, and many of these individuals are not being properly diagnosed. This …
Diagnosis and detection of pneumonia using weak-label based on X-ray images: a multi-center study
K Guo, J Cheng, K Li, L Wang, Y Lv, D Cao - BMC Medical Imaging, 2023 - Springer
Purpose Development and assessment the deep learning weakly supervised algorithm for
the classification and detection pneumonia via X-ray. Methods This retrospective study …
the classification and detection pneumonia via X-ray. Methods This retrospective study …
Patient-independent seizure detection based on long-term iEEG and a novel lightweight CNN
X Si, Z Yang, X Zhang, Y Sun, W Jin… - Journal of Neural …, 2023 - iopscience.iop.org
Objective. Patient-dependent seizure detection based on intracranial
electroencephalography (iEEG) has made significant progress. However, due to the …
electroencephalography (iEEG) has made significant progress. However, due to the …
Predicting plant growth and development using time-series images
C Wang, W Pan, X Song, H Yu, J Zhu, P Liu, X Li - Agronomy, 2022 - mdpi.com
Early prediction of the growth and development of plants is important for the intelligent
breeding process, yet accurate prediction and simulation of plant phenotypes is difficult. In …
breeding process, yet accurate prediction and simulation of plant phenotypes is difficult. In …