AIMC Topic: Algorithms

Clear Filters Showing 12541 to 12550 of 28713 articles

Deep Learning, Mining, and Collaborative Clustering to Identify Flexible Daily Activities Patterns.

Sensors (Basel, Switzerland)
The monitoring of the daily life activities routine is beneficial, especially in old age. It can provide relevant information on the person's health state and wellbeing and can help identify deviations that signal care deterioration or incidents that...

The Classification of Rice Blast Resistant Seed Based on Ranman Spectroscopy and SVM.

Molecules (Basel, Switzerland)
Rice blast is a serious threat to rice yield. Breeding disease-resistant varieties is one of the most economical and effective ways to prevent damage from rice blast. The traditional identification of resistant rice seeds has some shortcoming, such a...

Can deep learning improve image quality of low-dose CT: a prospective study in interstitial lung disease.

European radiology
OBJECTIVES: To investigate whether deep learning reconstruction (DLR) could keep image quality and reduce radiation dose in interstitial lung disease (ILD) patients compared with HRCT reconstructed with hybrid iterative reconstruction (hybrid-IR).

Sharing Rewards Undermines Coordinated Hunting.

Journal of computational biology : a journal of computational molecular cell biology
Coordinated hunting is widely observed in animals, and sharing rewards is often considered a major incentive for its success. While current theories about the role played by sharing in coordinated hunting are based on correlational evidence, we revea...

Speckle-Based Optical Cryptosystem and its Application for Human Face Recognition via Deep Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Face recognition has become ubiquitous for authentication or security purposes. Meanwhile, there are increasing concerns about the privacy of face images, which are sensitive biometric data and should be protected. Software-based cryptosystems are wi...

Impact of an artificial intelligence deep-learning reconstruction algorithm for CT on image quality and potential dose reduction: A phantom study.

Medical physics
BACKGROUND: Recently, computed tomography (CT) manufacturers have developed deep-learning-based reconstruction algorithms to compensate for the limitations of iterative reconstruction (IR) algorithms, such as image smoothing and the spatial resolutio...

Optical sensors and machine learning algorithms in sensor-based material flow characterization for mechanical recycling processes: A systematic literature review.

Waste management (New York, N.Y.)
Digital technologies hold enormous potential for improving the performance of future-generation sorting and processing plants; however, this potential remains largely untapped. Improved sensor-based material flow characterization (SBMC) methods could...

Rational Design of Field-Effect Sensors Using Partial Differential Equations, Bayesian Inversion, and Artificial Neural Networks.

Sensors (Basel, Switzerland)
Silicon nanowire field-effect transistors are promising devices used to detect minute amounts of different biological species. We introduce the theoretical and computational aspects of forward and backward modeling of biosensitive sensors. Firstly, w...

Drowsiness Detection Using Ocular Indices from EEG Signal.

Sensors (Basel, Switzerland)
Drowsiness is one of the main causes of road accidents and endangers the lives of road users. Recently, there has been considerable interest in utilizing features extracted from electroencephalography (EEG) signals to detect driver drowsiness. Howeve...

Model architecture can transform catastrophic forgetting into positive transfer.

Scientific reports
The work of McCloskey and Cohen popularized the concept of catastrophic interference. They used a neural network that tried to learn addition using two groups of examples as two different tasks. In their case, learning the second task rapidly deterio...