AIMC Topic: Neural Networks, Computer

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What is neurorepresentationalism? From neural activity and predictive processing to multi-level representations and consciousness.

Behavioural brain research
This review provides an update on Neurorepresentationalism, a theoretical framework that defines conscious experience as multimodal, situational survey and explains its neural basis from brain systems constructing best-guess representations of sensat...

Spatial Attention-Based 3D Graph Convolutional Neural Network for Sign Language Recognition.

Sensors (Basel, Switzerland)
Sign language is the main channel for hearing-impaired people to communicate with others. It is a visual language that conveys highly structured components of manual and non-manual parameters such that it needs a lot of effort to master by hearing pe...

Remaining Useful Life Prediction Method for Bearings Based on LSTM with Uncertainty Quantification.

Sensors (Basel, Switzerland)
To reduce the economic losses caused by bearing failures and prevent safety accidents, it is necessary to develop an effective method to predict the remaining useful life (RUL) of the rolling bearing. However, the degradation inside the bearing is di...

A Low-Power Analog Processor-in-Memory-Based Convolutional Neural Network for Biosensor Applications.

Sensors (Basel, Switzerland)
This paper presents an on-chip implementation of an analog processor-in-memory (PIM)-based convolutional neural network (CNN) in a biosensor. The operator was designed with low power to implement CNN as an on-chip device on the biosensor, which consi...

A Review of Image Processing Techniques for Deepfakes.

Sensors (Basel, Switzerland)
Deep learning is used to address a wide range of challenging issues including large data analysis, image processing, object detection, and autonomous control. In the same way, deep learning techniques are also used to develop software and techniques ...

Research on Multi-Sensor Fusion Indoor Fire Perception Algorithm Based on Improved TCN.

Sensors (Basel, Switzerland)
Indoor fires cause huge casualties and economic losses worldwide. Thus, it is critical to quickly and accurately perceive the fire. In this work, an indoor fire perception algorithm based on multi-sensor fusion was proposed. Firstly, the sensor data ...

Using Deep Neural Networks for Human Fall Detection Based on Pose Estimation.

Sensors (Basel, Switzerland)
Requests for caring for and monitoring the health and safety of older adults are increasing nowadays and form a topic of great social interest. One of the issues that lead to serious concerns is human falls, especially among aged people. Computer vis...

Selfee, self-supervised features extraction of animal behaviors.

eLife
Fast and accurately characterizing animal behaviors is crucial for neuroscience research. Deep learning models are efficiently used in laboratories for behavior analysis. However, it has not been achieved to use an end-to-end unsupervised neural netw...

RA V-Net: deep learning network for automated liver segmentation.

Physics in medicine and biology
Segmenting liver from CT images is the first step for doctors to diagnose a patient's disease. Processing medical images with deep learning models has become a current research trend. Although it can automate segmenting region of interest of medical ...

Analysis of Equilibria for a Class of Recurrent Neural Networks With Two Subnetworks.

IEEE transactions on cybernetics
This article is concerned with the problem of the number and dynamical properties of equilibria for a class of connected recurrent networks with two switching subnetworks. In this network model, parameters serve as switches that allow two subnetworks...