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Neural Networks, Computer - AI Medical Compendium

AIMC Topic: Neural Networks, Computer

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An effective automatic segmentation of abdominal adipose tissue using a convolution neural network.

Diabetes & metabolic syndrome
BACKGROUND AND AIMS: Computer-aided diagnosis and prognosis rely heavily on fully automatic segmentation of abdominal fat tissue using Emission Tomography images. The identification of subcutaneous adipose tissue (SAT) and visceral adipose tissue (VA...

Digital computing through randomness and order in neural networks.

Proceedings of the National Academy of Sciences of the United States of America
We propose that coding and decoding in the brain are achieved through digital computation using three principles: relative ordinal coding of inputs, random connections between neurons, and belief voting. Due to randomization and despite the coarsenes...

Demod-CNN: A Robust Deep Learning Approach for Intelligent Reflecting Surface-Assisted Multiuser MIMO Communication.

Sensors (Basel, Switzerland)
The intelligent reflecting surface (IRS) is a novel and innovative communication technology that aims at the control of the wireless environment. The IRS is considered as a promising technology for sixth-generation wireless communication. In the last...

Design of Convolutional Neural Network Processor Based on FPGA Resource Multiplexing Architecture.

Sensors (Basel, Switzerland)
As CNNs are widely used in fields such as image classification and target detection, the total number of parameters and computation of the models is gradually increasing. In addition, the requirements on hardware resources and power consumption for d...

Intelligent yield estimation for tomato crop using SegNet with VGG19 architecture.

Scientific reports
Yield estimation (YE) of the crop is one of the main tasks in fruit management and marketing. Based on the results of YE, the farmers can make a better decision on the harvesting period, prevention strategies for crop disease, subsequent follow-up fo...

Particle Swarm Optimized Fuzzy CNN With Quantitative Feature Fusion for Ultrasound Image Quality Identification.

IEEE journal of translational engineering in health and medicine
Inherently ultrasound images are susceptible to noise which leads to several image quality issues. Hence, rating of an image's quality is crucial since diagnosing diseases requires accurate and high-quality ultrasound images. This research presents a...

Automated Recognition of Cancer Tissues through Deep Learning Framework from the Photoacoustic Specimen.

Contrast media & molecular imaging
The fast advancement of biomedical research technology has expanded and enhanced the spectrum of diagnostic instruments. Various research groups have found optical imaging, ultrasonic imaging, and magnetic resonance imaging to create multifunctional ...

Extraction and Analysis of Foot Bone Shape Features Based on Deep Learning.

Computational and mathematical methods in medicine
With the rapid development of artificial intelligence, more and more researchers and research institutions begin to pay attention to the bone feature recognition field. Human bone movement is very complex, and human bone shape recognition technology ...

Pan-Logical Probabilistic Algorithms Based on Convolutional Neural Networks.

Computational intelligence and neuroscience
A brand-new kind of flexible logic system called universal logic aims to address a variety of uncertain problems. In this study, the role of convolutional neural networks in assessing probabilistic pan-logic algorithms is investigated. A generic logi...

Application of Higher Education Management in Colleges and Universities by Deep Learning.

Computational intelligence and neuroscience
The development of artificial intelligence (AI) has brought great convenience to people and has been widely used in the field of education. To monitor the classroom status of college students in real time and achieve the purpose of balanced distribut...