AIMC Topic: Neural Networks, Computer

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Signal-to-signal neural networks for improved spike estimation from calcium imaging data.

PLoS computational biology
Spiking information of individual neurons is essential for functional and behavioral analysis in neuroscience research. Calcium imaging techniques are generally employed to obtain activities of neuronal populations. However, these techniques result i...

Anam-Net: Anamorphic Depth Embedding-Based Lightweight CNN for Segmentation of Anomalies in COVID-19 Chest CT Images.

IEEE transactions on neural networks and learning systems
Chest computed tomography (CT) imaging has become indispensable for staging and managing coronavirus disease 2019 (COVID-19), and current evaluation of anomalies/abnormalities associated with COVID-19 has been performed majorly by the visual score. T...

Metaheuristic-based Deep COVID-19 Screening Model from Chest X-Ray Images.

Journal of healthcare engineering
COVID-19 has affected the whole world drastically. A huge number of people have lost their lives due to this pandemic. Early detection of COVID-19 infection is helpful for treatment and quarantine. Therefore, many researchers have designed a deep lea...

Convolutional neural network model based on radiological images to support COVID-19 diagnosis: Evaluating database biases.

PloS one
As SARS-CoV-2 has spread quickly throughout the world, the scientific community has spent major efforts on better understanding the characteristics of the virus and possible means to prevent, diagnose, and treat COVID-19. A valid approach presented i...

A fault diagnosis method based on Auxiliary Classifier Generative Adversarial Network for rolling bearing.

PloS one
Rolling bearing fault diagnosis is one of the challenging tasks and hot research topics in the condition monitoring and fault diagnosis of rotating machinery. However, in practical engineering applications, the working conditions of rotating machiner...

A message-passing multi-task architecture for the implicit event and polarity detection.

PloS one
Implicit sentiment analysis is a challenging task because the sentiment of a text is expressed in a connotative manner. To tackle this problem, we propose to use textual events as a knowledge source to enrich network representations. To consider task...

Individualized Gait Generation for Rehabilitation Robots Based on Recurrent Neural Networks.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Individualized reference gait patterns for lower limb rehabilitation robots can greatly improve the effectiveness of rehabilitation. However, previous methods can only generate customized gait patterns at several fixed discrete walking speeds and gen...

Basic theorem and global exponential stability of differential-algebraic neural networks with delay.

Neural networks : the official journal of the International Neural Network Society
A differential-algebraic neural network (DANN) with delay (DDANN) is proposed. Firstly, the global existence and uniqueness theorems are established for a DDANN, respectively. Next, a new differential-algebraic inequality is established. Then, a theo...

A convolutional neural network architecture for the recognition of cutaneous manifestations of COVID-19.

Dermatologic therapy
During the COVID-19 pandemic, dermatologists reported an array of different cutaneous manifestations of the disease. It is challenging to discriminate COVID-19-related cutaneous manifestations from other closely resembling skin lesions. The aim of th...

DNN-m6A: A Cross-Species Method for Identifying RNA N6-Methyladenosine Sites Based on Deep Neural Network with Multi-Information Fusion.

Genes
As a prevalent existing post-transcriptional modification of RNA, N6-methyladenosine (m6A) plays a crucial role in various biological processes. To better radically reveal its regulatory mechanism and provide new insights for drug design, the accurat...