AIMC Topic: Neural Networks, Computer

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Fluorescence hyperspectral imaging for detection of selenium content in lettuce leaves under cadmium-free and cadmium environments.

Food chemistry
This study aimed to investigate the feasibility of detecting selenium content in lettuce leaves under complex environments (cadmium-free and cadmium environments) using fluorescence hyperspectral imaging (FHSI). Accordingly, multimodal difference-awa...

Advancements in automated nuclei segmentation for histopathology using you only look once-driven approaches: A systematic review.

Computers in biology and medicine
Histopathology image analysis plays a pivotal role in disease diagnosis and treatment planning, relying heavily on accurate nuclei segmentation for extracting vital cellular information. In recent years, artificial intelligence (AI) and in particular...

Soil and crop interaction analysis for yield prediction with satellite imagery and deep learning techniques for the coastal regions.

Journal of environmental management
Crop yield is a significant factor in world income and poverty alleviation as well as food production through agriculture. Conventional crop yield forecasting approaches that employ subjective estimates including farmers' perceptions are imprecise an...

Convolutional Neural Network Models for Visual Classification of Pressure Ulcer Stages: Cross-Sectional Study.

JMIR medical informatics
BACKGROUND: Pressure injuries (PIs) pose a negative health impact and a substantial economic burden on patients and society. Accurate staging is crucial for treating PIs. Owing to the diversity in the clinical manifestations of PIs and the lack of ob...

Thyroid nodule classification in ultrasound imaging using deep transfer learning.

BMC cancer
BACKGROUND: The accurate diagnosis of thyroid nodules represents a critical and frequently encountered challenge in clinical practice, necessitating enhanced precision in diagnostic methodologies. In this study, we investigate the predictive efficacy...

Mpox-XDE: an ensemble model utilizing deep CNN and explainable AI for monkeypox detection and classification.

BMC infectious diseases
The daily surge in cases in many nations has made the growing number of human monkeypox (Mpox) cases an important global concern. Therefore, it is imperative to identify Mpox early to prevent its spread. The majority of studies on Mpox identification...

Research on wheelchair form design based on Kansei engineering and GWO-BP neural network.

Scientific reports
With the increasing emphasis on humanistic care in society, consumers are no longer only concerned about the functional needs of products but also about the spiritual, cultural, and emotional needs that products bring to people. This study proposes a...

An ensemble approach using multidimensional convolutional neural networks in wavelet domain for schizophrenia classification from sMRI data.

Scientific reports
Schizophrenia is a complicated mental condition marked by disruptions in thought processes, perceptions, and emotional responses, which can cause severe impairment in everyday functioning. sMRI is a non-invasive neuroimaging technology that visualize...

IoT powered RNN for improved human activity recognition with enhanced localization and classification.

Scientific reports
Human activity recognition (HAR) and localization are green research areas of the modern era that are being propped up by smart devices. But the data acquired from the sensors embedded in smart devices, contain plenty of noise that makes it indispens...