AIMC Topic: Algorithms

Clear Filters Showing 21101 to 21110 of 28713 articles

Application of Deep Learning Architectures for Accurate and Rapid Detection of Internal Mechanical Damage of Blueberry Using Hyperspectral Transmittance Data.

Sensors (Basel, Switzerland)
Deep learning has become a widely used powerful tool in many research fields, although not much so yet in agriculture technologies. In this work, two deep convolutional neural networks (CNN), viz. Residual Network (ResNet) and its improved version na...

Mixed deep learning and natural language processing method for fake-food image recognition and standardization to help automated dietary assessment.

Public health nutrition
OBJECTIVE: The present study tested the combination of an established and a validated food-choice research method (the 'fake food buffet') with a new food-matching technology to automate the data collection and analysis.

KIKI-net: cross-domain convolutional neural networks for reconstructing undersampled magnetic resonance images.

Magnetic resonance in medicine
PURPOSE: To demonstrate accurate MR image reconstruction from undersampled k-space data using cross-domain convolutional neural networks (CNNs) METHODS: Cross-domain CNNs consist of 3 components: (1) a deep CNN operating on the k-space (KCNN), (2) a ...

TopP-S: Persistent homology-based multi-task deep neural networks for simultaneous predictions of partition coefficient and aqueous solubility.

Journal of computational chemistry
Aqueous solubility and partition coefficient are important physical properties of small molecules. Accurate theoretical prediction of aqueous solubility and partition coefficient plays an important role in drug design and discovery. The prediction ac...

A deep Boltzmann machine-driven level set method for heart motion tracking using cine MRI images.

Medical image analysis
Heart motion tracking for radiation therapy treatment planning can result in effective motion management strategies to minimize radiation-induced cardiotoxicity. However, automatic heart motion tracking is challenging due to factors that include the ...

Spiking neural networks for handwritten digit recognition-Supervised learning and network optimization.

Neural networks : the official journal of the International Neural Network Society
We demonstrate supervised learning in Spiking Neural Networks (SNNs) for the problem of handwritten digit recognition using the spike triggered Normalized Approximate Descent (NormAD) algorithm. Our network that employs neurons operating at sparse bi...

The Growing Curvilinear Component Analysis (GCCA) neural network.

Neural networks : the official journal of the International Neural Network Society
Big high dimensional data is becoming a challenging field of research. There exist a lot of techniques which infer information. However, because of the curse of dimensionality, a necessary step is the dimensionality reduction (DR) of the information....

A Matter of Time: Faster Percolator Analysis via Efficient SVM Learning for Large-Scale Proteomics.

Journal of proteome research
Percolator is an important tool for greatly improving the results of a database search and subsequent downstream analysis. Using support vector machines (SVMs), Percolator recalibrates peptide-spectrum matches based on the learned decision boundary b...

Emotion computing using Word Mover's Distance features based on Ren_CECps.

PloS one
In this paper, we propose an emotion separated method(SeTF·IDF) to assign the emotion labels of sentences with different values, which has a better visual effect compared with the values represented by TF·IDF in the visualization of a multi-label Chi...