AIMC Topic: Algorithms

Clear Filters Showing 14051 to 14060 of 28713 articles

Enhancing Crop Yield Prediction Utilizing Machine Learning on Satellite-Based Vegetation Health Indices.

Sensors (Basel, Switzerland)
Accurate crop yield forecasting is essential in the food industry's decision-making process, where vegetation condition index (VCI) and thermal condition index (TCI) coupled with machine learning (ML) algorithms play crucial roles. The drawback, howe...

Multichannel Two-Dimensional Convolutional Neural Network Based on Interactive Features and Group Strategy for Chinese Sentiment Analysis.

Sensors (Basel, Switzerland)
In Chinese sentiment analysis tasks, many existing methods tend to use recurrent neural networks (e.g., long short-term memory networks and gated recurrent units) and standard one-dimensional convolutional neural networks (1D-CNN) to extract features...

The inclusion of augmented intelligence in medicine: A framework for successful implementation.

Cell reports. Medicine
Artificial intelligence (AI) algorithms are being applied across a large spectrum of everyday life activities. The implementation of AI algorithms in clinical practice has been met with some skepticism and concern, mainly because of the uneasiness th...

CellSeg: a robust, pre-trained nucleus segmentation and pixel quantification software for highly multiplexed fluorescence images.

BMC bioinformatics
BACKGROUND: Algorithmic cellular segmentation is an essential step for the quantitative analysis of highly multiplexed tissue images. Current segmentation pipelines often require manual dataset annotation and additional training, significant paramete...

Radioactive hot-spot localisation and identification using deep learning.

Journal of radiological protection : official journal of the Society for Radiological Protection
The detection of radioactive hot-spots and the identification of the radionuclides present have been a challenge for the security sector, especially in situations involving chemical, biological, radiological, nuclear and explosive threats, as well as...

Fusion-Based Deep Learning with Nature-Inspired Algorithm for Intracerebral Haemorrhage Diagnosis.

Journal of healthcare engineering
Natural computing refers to computational processes observed in nature and human-designed computing inspired by nature. In recent times, data fusion in the healthcare sector becomes a challenging issue, and it needs to be resolved. At the same time, ...

Research on Music Style Classification Based on Deep Learning.

Computational and mathematical methods in medicine
Music style is one of the important labels for music classification, and the current music style classification methods extract features such as rhythm and timbre of music and use classifiers to achieve classification. The classification accuracy is ...

Tourism Demand Forecast Based on Adaptive Neural Network Technology in Business Intelligence.

Computational intelligence and neuroscience
In order to improve the effect of tourism demand forecast, the commercial development of the tourism industry, and the actual experience of users, this paper uses adaptive neural network technology to conduct tourism demand forecast analysis. Moreove...

Deep Learning and Improved HMM Training Algorithm and Its Analysis in Facial Expression Recognition of Sports Athletes.

Computational intelligence and neuroscience
Facial expressions are an auxiliary embodiment of information conveyed in the communication between people. Facial expressions can not only convey the semantic information that people want to express but also convey the emotional state of the speaker...

Prediction model of acute kidney injury induced by cisplatin in older adults using a machine learning algorithm.

PloS one
BACKGROUND: Early detection and prediction of cisplatin-induced acute kidney injury (Cis-AKI) are essential for the management of patients on chemotherapy with cisplatin. This study aimed to evaluate the performance of a prediction model for Cis-AKI.