AIMC Topic: Neural Networks, Computer

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Lead federated neuromorphic learning for wireless edge artificial intelligence.

Nature communications
In order to realize the full potential of wireless edge artificial intelligence (AI), very large and diverse datasets will often be required for energy-demanding model training on resource-constrained edge devices. This paper proposes a lead federate...

A deep learning approach to estimate pulse rate by remote photoplethysmography.

Physiological measurement
This study proposes a U-net shaped Deep Neural Network (DNN) model to extract remote photoplethysmography (rPPG) signals from skin color signals to estimate Pulse Rate (PR).Three input window sizes are used in the DNN: 256 samples (5.12 s), 512 sampl...

Deep active learning for suggestive segmentation of biomedical image stacks via optimisation of Dice scores and traced boundary length.

Medical image analysis
Manual segmentation of stacks of 2D biomedical images (e.g., histology) is a time-consuming task which can be sped up with semi-automated techniques. In this article, we present a suggestive deep active learning framework that seeks to minimise the a...

BO-ALLCNN: Bayesian-Based Optimized CNN for Acute Lymphoblastic Leukemia Detection in Microscopic Blood Smear Images.

Sensors (Basel, Switzerland)
Acute lymphoblastic leukemia (ALL) is a deadly cancer characterized by aberrant accumulation of immature lymphocytes in the blood or bone marrow. Effective treatment of ALL is strongly associated with the early diagnosis of the disease. Current pract...

Application of PSO-BPNN-PID Controller in Nutrient Solution EC Precise Control System: Applied Research.

Sensors (Basel, Switzerland)
In this paper, we present a nutrient solution control system, designing a nutrient solution electrical conductivity (EC) sensing system composed of multiple long-range radio (LoRa) slave nodes, narrow-band Internet of Things (NB-IoT) master nodes, an...

Deep neural network prediction of modified stepped double-slope solar still with a cotton wick and cobalt oxide nanofluid.

Environmental science and pollution research international
This research work intends to enhance the stepped double-slope solar still performance through an experimental assessment of combining linen wicks and cobalt oxide nanoparticles to the stepped double-slope solar still to improve the water evaporation...

Deep Unsupervised Domain Adaptation with Time Series Sensor Data: A Survey.

Sensors (Basel, Switzerland)
Sensors are devices that output signals for sensing physical phenomena and are widely used in all aspects of our social production activities. The continuous recording of physical parameters allows effective analysis of the operational status of the ...

Estimation of Greenhouse Lettuce Growth Indices Based on a Two-Stage CNN Using RGB-D Images.

Sensors (Basel, Switzerland)
Growth indices can quantify crop productivity and establish optimal environmental, nutritional, and irrigation control strategies. A convolutional neural network (CNN)-based model is presented for estimating various growth indices (i.e., fresh weight...

Deep Learning-Based Networks for Detecting Anomalies in Chest X-Rays.

BioMed research international
X-ray images aid medical professionals in the diagnosis and detection of pathologies. They are critical, for example, in the diagnosis of pneumonia, the detection of masses, and, more recently, the detection of COVID-19-related conditions. The chest ...

Construction of Emergency Procurement System and System Improvement Based on Convolutional Neural Network.

Computational intelligence and neuroscience
At this stage, countries around the world have their own operating management model for the procurement system of emergency equipment. This article analyzes the influencing factors affecting the operation of the emergency procurement system through a...