AIMC Topic: Neural Networks, Computer

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Specific Radar Recognition Based on Characteristics of Emitted Radio Waveforms Using Convolutional Neural Networks.

Sensors (Basel, Switzerland)
With the increasing complexity of the electromagnetic environment and continuous development of radar technology we can expect a large number of modern radars using agile waveforms to appear on the battlefield in the near future. Effectively identify...

Noise-trained deep neural networks effectively predict human vision and its neural responses to challenging images.

PLoS biology
Deep neural networks (DNNs) for object classification have been argued to provide the most promising model of the visual system, accompanied by claims that they have attained or even surpassed human-level performance. Here, we evaluated whether DNNs ...

A Multi-functional Memristive Pavlov Associative Memory Circuit Based on Neural Mechanisms.

IEEE transactions on biomedical circuits and systems
Pavlov conditioning is a typical associative memory, which involves associative learning between the gustatory and auditory cortex, known as Pavlov associative memory. Inspired by neural mechanisms and biological phenomena of Pavlov associative memor...

Risk Prediction by Using Artificial Neural Network in Global Software Development.

Computational intelligence and neuroscience
The demand for global software development is growing. The nonavailability of software experts at one place or a country is the reason for the increase in the scope of global software development. Software developers who are located in different part...

A Comparative Performance Assessment of Optimized Multilevel Ensemble Learning Model with Existing Classifier Models.

Big data
To predict the class level of any classification problem, predictive models are used and mostly a single predictive model is built to predict the class level of any classification problem; current research considers multiple predictive models to pred...

Artificial intelligence for the assessment of bowel preparation.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: A reliable assessment of bowel preparation is important to ensure high-quality colonoscopy. Current bowel preparation scoring systems are limited by interobserver variability. This study aimed to demonstrate objective assessment ...

Transfer learning for spatio-temporal transferability of real-time crash prediction models.

Accident; analysis and prevention
Real-time crash prediction is a heavily studied area given their potential applications in proactive traffic safety management in which a plethora of statistical and machine learning (ML) models have been developed to predict traffic crashes in real-...

Predicting the Travel Distance of Patients to Access Healthcare Using Deep Neural Networks.

IEEE journal of translational engineering in health and medicine
OBJECTIVE: Improving geographical access remains a key issue in determining the sufficiency of regional medical resources during health policy design. However, patient choices can be the result of the complex interactivity of various factors. The aim...

Vocal cord lesions classification based on deep convolutional neural network and transfer learning.

Medical physics
PURPOSE: Laryngoscopy, the most common diagnostic method for vocal cord lesions (VCLs), is based mainly on the visual subjective inspection of otolaryngologists. This study aimed to establish a highly objective computer-aided VCLs diagnosis system ba...

Activating Silent Synapses in Sulfurized Indium Selenide for Neuromorphic Computing.

ACS applied materials & interfaces
The transformation from silent to functional synapses is accompanied by the evolutionary process of human brain development and is essential to hardware implementation of the evolutionary artificial neural network but remains a challenge for mimickin...