AIMC Topic: Neural Networks, Computer

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Bio-instantiated recurrent neural networks: Integrating neurobiology-based network topology in artificial networks.

Neural networks : the official journal of the International Neural Network Society
Biological neuronal networks (BNNs) are a source of inspiration and analogy making for researchers that focus on artificial neuronal networks (ANNs). Moreover, neuroscientists increasingly use ANNs as a model for the brain. Despite certain similariti...

Joint fully convolutional and graph convolutional networks for weakly-supervised segmentation of pathology images.

Medical image analysis
Tissue/region segmentation of pathology images is essential for quantitative analysis in digital pathology. Previous studies usually require full supervision (e.g., pixel-level annotation) which is challenging to acquire. In this paper, we propose a ...

Deep neural network approach for estimating the three-dimensional human center of mass using joint angles.

Journal of biomechanics
Human body center of mass location plays an essential role in physical therapy, especially in investigating a subject's capability to maintain balance. However, its estimation can be a very complex, costly, and time-consuming process. To overcome the...

A Multi-Objective Evolutionary Approach Based on Graph-in-Graph for Neural Architecture Search of Convolutional Neural Networks.

International journal of neural systems
With the development of deep learning, the design of an appropriate network structure becomes fundamental. In recent years, the successful practice of Neural Architecture Search (NAS) has indicated that an automated design of the network structure ca...

Spin-Orbit Torque-Induced Domain Nucleation for Neuromorphic Computing.

Advanced materials (Deerfield Beach, Fla.)
Neuromorphic computing has become an increasingly popular approach for artificial intelligence because it can perform cognitive tasks more efficiently than conventional computers. However, it remains challenging to develop dedicated hardware for arti...

An SVM approach towards breast cancer classification from H&E-stained histopathology images based on integrated features.

Medical & biological engineering & computing
Breast cancer is one among the most frequent reasons of women's death worldwide. Nowadays, healthcare informatics is mainly focussing on the classification of breast cancer images, due to the lethal nature of this cancer. There are chances of inter- ...

A Method for Real-Time Fault Detection of Liquid Rocket Engine Based on Adaptive Genetic Algorithm Optimizing Back Propagation Neural Network.

Sensors (Basel, Switzerland)
A real-time fault diagnosis method utilizing an adaptive genetic algorithm to optimize a back propagation (BP) neural network is intended to achieve real-time fault detection of a liquid rocket engine (LRE). In this paper, the authors employ an adapt...

Menopausal Women's Health Care Method Based on Computer Nursing Diagnosis Intelligent System.

Journal of healthcare engineering
Taking into account the current feature extraction speed and recognition effect of intelligent diagnosis of menopausal women's health care behavior, this paper proposes to use a cross-layer convolutional neural network to extract behavior features au...

Use of Machine Learning for the Estimation of Down- and Up-Link Field Exposure in Multi-Source Indoor WiFi Scenarios.

Bioelectromagnetics
A novel Machine Learning (ML) method based on Neural Networks (NN) is proposed to assess radio-frequency (RF) exposure generated by WiFi sources in indoor scenarios. The aim was to build an NN capable of addressing the complexity and variability of r...

Logistic matrix factorisation and generative adversarial neural network-based method for predicting drug-target interactions.

Molecular diversity
Identifying drug-target protein association pairs is a prerequisite and a crucial task in drug discovery and development. Numerous computational models, based on different assumptions and algorithms, have been proposed as an alternative to the labori...