AIMC Topic: Deep Learning

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Water quality forecasting based on data decomposition, fuzzy clustering and deep learning neural network.

Environmental pollution (Barking, Essex : 1987)
Water quality forecasting can provide useful information for public health protection and support water resources management. In order to forecast water quality more accurately, this paper proposes a novel hybrid model by combining data decomposition...

A fast multi-source information fusion strategy based on deep learning for species identification of boletes.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Wild mushroom market is an important economic source of Yunnan province in China, and its wild mushroom resources are also valuable wealth in the world. This work will put forward a method of species identification and optimize the method in order to...

High-Precision Intelligent Cancer Diagnosis Method: 2D Raman Figures Combined with Deep Learning.

Analytical chemistry
Raman spectroscopy, as a label-free detection technology, has been widely used in tumor diagnosis. However, most tumor diagnosis procedures utilize multivariate statistical analysis methods for classification, which poses a major bottleneck toward ac...

Metaheuristics based COVID-19 detection using medical images: A review.

Computers in biology and medicine
Many countries in the world have been facing the rapid spread of COVID-19 since February 2020. There is a dire need for efficient and cheap automated diagnosis systems that can reduce the pressure on healthcare systems. Extensive research is being do...

An automated diagnosis and classification of COVID-19 from chest CT images using a transfer learning-based convolutional neural network.

Computers in biology and medicine
Researchers have developed more intelligent, highly responsive, and efficient detection methods owing to the COVID-19 demands for more widespread diagnosis. The work done deals with developing an AI-based framework that can help radiologists and othe...

Unified Deep Learning Model for Multitask Reaction Predictions with Explanation.

Journal of chemical information and modeling
There is significant interest and importance to develop robust machine learning models to assist organic chemistry synthesis. Typically, task-specific machine learning models for distinct reaction prediction tasks have been developed. In this work, w...

Melanoma segmentation using deep learning with test-time augmentations and conditional random fields.

Scientific reports
In a computer-aided diagnostic (CAD) system for skin lesion segmentation, variations in shape and size of the skin lesion makes the segmentation task more challenging. Lesion segmentation is an initial step in CAD schemes as it leads to low error rat...

Predicting streamflow in Peninsular Malaysia using support vector machine and deep learning algorithms.

Scientific reports
Floods and droughts are environmental phenomena that occur in Peninsular Malaysia due to extreme values of streamflow (SF). Due to this, the study of SF prediction is highly significant for the purpose of municipal and environmental damage mitigation...

Optimal Deep Learning Enabled Prostate Cancer Detection Using Microarray Gene Expression.

Journal of healthcare engineering
Prostate cancer is the main cause of death over the globe. Earlier detection and classification of cancer is highly important to improve patient health. Previous studies utilized statistical and machine learning (ML) techniques for prostate cancer de...

Deep learning for 1-bit compressed sensing-based superimposed CSI feedback.

PloS one
In frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems, 1-bit compressed sensing (CS)-based superimposed channel state information (CSI) feedback has shown many advantages, while still faces many challenges, such ...