AIMC Topic: Neural Networks, Computer

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On the estimation of sugars concentrations using Raman spectroscopy and artificial neural networks.

Food chemistry
In this paper, we present an analysis of the performance of Raman spectroscopy, combined with feed-forward neural networks (FFNN), for the estimation of concentration percentages of glucose, sucrose, and fructose in water solutions. Indeed, we analys...

Visual question answering based on local-scene-aware referring expression generation.

Neural networks : the official journal of the International Neural Network Society
Visual question answering requires a deep understanding of both images and natural language. However, most methods mainly focus on visual concept; such as the relationships between various objects. The limited use of object categories combined with t...

Synchronization criteria of delayed inertial neural networks with generally Markovian jumping.

Neural networks : the official journal of the International Neural Network Society
In this paper, the synchronization problem of inertial neural networks with time-varying delays and generally Markovian jumping is investigated. The second order differential equations are transformed into the first-order differential equations by ut...

Residual Neural Network precisely quantifies dysarthria severity-level based on short-duration speech segments.

Neural networks : the official journal of the International Neural Network Society
Recently, we have witnessed Deep Learning methodologies gaining significant attention for severity-based classification of dysarthric speech. Detecting dysarthria, quantifying its severity, are of paramount importance in various real-life application...

Deep learning techniques have significantly impacted protein structure prediction and protein design.

Current opinion in structural biology
Protein structure prediction and design can be regarded as two inverse processes governed by the same folding principle. Although progress remained stagnant over the past two decades, the recent application of deep neural networks to spatial constrai...

Double-flow convolutional neural network for rapid large field of view Fourier ptychographic reconstruction.

Journal of biophotonics
Fourier ptychographic microscopy is a promising imaging technique which can circumvent the space-bandwidth product of the system and achieve a reconstruction result with wide field-of-view (FOV), high-resolution and quantitative phase information. Ho...

Deep Consensus Network: Aggregating predictions to improve object detection in microscopy images.

Medical image analysis
Detection of cells and particles in microscopy images is a common and challenging task. In recent years, detection approaches in computer vision achieved remarkable improvements by leveraging deep learning. Microscopy images pose challenges like smal...

Intraoral radiograph anatomical region classification using neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: Dental radiography represents 13% of all radiological diagnostic imaging. Eliminating the need for manual classification of digital intraoral radiographs could be especially impactful in terms of time savings and metadata quality. However, a...

Generative Adversarial Learning of Protein Tertiary Structures.

Molecules (Basel, Switzerland)
Protein molecules are inherently dynamic and modulate their interactions with different molecular partners by accessing different tertiary structures under physiological conditions. Elucidating such structures remains challenging. Current momentum in...

LLAD: Life-Log Anomaly Detection Based on Recurrent Neural Network LSTM.

Journal of healthcare engineering
Life-Log is a term used for the daily monitoring of health conditions and recognizing anomalies from data generated by sensor devices. The development of smart sensors enables collection of health data, which can be considered as a solution to risks ...