AIMC Topic: Neural Networks, Computer

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Industrial Soft Sensor Optimized by Improved PSO: A Deep Representation-Learning Approach.

Sensors (Basel, Switzerland)
Soft sensors based on deep learning approaches are growing in popularity due to their ability to extract high-level features from training, improving soft sensors' performance. In the training process of such a deep model, the set of hyperparameters ...

Artificial intelligence (AI) diagnostic tools: utilizing a convolutional neural network (CNN) to assess periodontal bone level radiographically-a retrospective study.

BMC oral health
BACKGROUND: The purpose of this investigation was to develop a computer-assisted detection system based on a deep convolutional neural network (CNN) algorithm and to evaluate the accuracy and usefulness of this system for the detection of alveolar bo...

ID-RDRL: a deep reinforcement learning-based feature selection intrusion detection model.

Scientific reports
Network assaults pose significant security concerns to network services; hence, new technical solutions must be used to enhance the efficacy of intrusion detection systems. Existing approaches pay insufficient attention to data preparation and inadeq...

Shale gas geological "sweet spot" parameter prediction method and its application based on convolutional neural network.

Scientific reports
Parameters such as gas content (GAS), porosity (PHI) and total organic carbon (TOC) are key parameters that reveal the shale gas geological "sweet spot" of reservoirs. However, the lack of a three-dimensional high-precision prediction method is not c...

Unsupervised classification of voltammetric data beyond principal component analysis.

Chemical communications (Cambridge, England)
In this study, we evaluate different apoproaches to unsupervised classification of cyclic voltammetric data, including Principal Component Analysis (PCA), t-distributed Stochastic Neighbour Embedding (t-SNE), Uniform Manifold Approximation and Projec...

Analysis of Smart Lung Tumour Detector and Stage Classifier Using Deep Learning Techniques with Internet of Things.

Computational intelligence and neuroscience
The use of artificial intelligence (AI) and the Internet of Things (IoT), which is a developing technology in medical applications that assists physicians in making more informed decisions regarding patients' courses of treatment, has become increasi...

Optimization of Artistic Image Segmentation Algorithm Based on Feed Forward Neural Network under Complex Background Environment.

Journal of environmental and public health
Based on the theory and application, this paper discusses the optimization of art image segmentation algorithm based on FFNN (Feed Forward Neural Network). In this paper, residual units are used in the corresponding stages of encoder and decoder, and...

Deep learning approaches based improved light weight U-Net with attention module for optic disc segmentation.

Physical and engineering sciences in medicine
Glaucoma is a major cause of blindness worldwide, and its early detection is essential for the timely management of the condition. Glaucoma-induced anomalies of the optic nerve head may cause variation in the Optic Disc (OD) size. Therefore, robust O...

Nucleophilicity Prediction Using Graph Neural Networks.

Journal of chemical information and modeling
The quantitative description between chemical reaction rates and nucleophilicity parameters plays a crucial role in organic chemistry. In this regard, the formula proposed by Mayr et al. and the constructed reactivity database are important represent...

Cooperative learning for multiview analysis.

Proceedings of the National Academy of Sciences of the United States of America
We propose a method for supervised learning with multiple sets of features ("views"). The multiview problem is especially important in biology and medicine, where "-omics" data, such as genomics, proteomics, and radiomics, are measured on a common se...