AIMC Topic: Neural Networks, Computer

Clear Filters Showing 17131 to 17140 of 31376 articles

The Use of Collections of Artificial Neural Networks to Improve the Control Quality of the Induction Soldering Process.

Sensors (Basel, Switzerland)
In industries that implement the technology of induction soldering, various sensors, including non-contact pyrometric ones, are widely used to control the technological process. The use of this type of sensor implies the need to choose a solution tha...

Video-Sensing Characterization for Hydrodynamic Features: Particle Tracking-Based Algorithm Supported by a Machine Learning Approach.

Sensors (Basel, Switzerland)
The efficient and reliable monitoring of the flow of water in open channels provides useful information for preventing water slow-downs due to the deposition of materials within the bed of the channel, which might lead to critical floods. A reliable ...

An Approximate GEMM Unit for Energy-Efficient Object Detection.

Sensors (Basel, Switzerland)
Edge computing brings artificial intelligence algorithms and graphics processing units closer to data sources, making autonomy and energy-efficient processing vital for their design. Approximate computing has emerged as a popular strategy for energy-...

Microbiome Preprocessing Machine Learning Pipeline.

Frontiers in immunology
BACKGROUND: 16S sequencing results are often used for Machine Learning (ML) tasks. 16S gene sequences are represented as feature counts, which are associated with taxonomic representation. Raw feature counts may not be the optimal representation for ...

Distributed optimal power flow.

PloS one
OBJECTIVE: The objectives of this paper are to 1) construct a new network model compatible with distributed computation, 2) construct the full optimal power flow (OPF) in a distributed fashion so that an effective, non-inferior solution can be found,...

Finite-time bipartite synchronization of switched competitive neural networks with time delay via quantized control.

ISA transactions
This article tackles the finite-time bipartite synchronization (FTBS) of coupled competitive neural networks (CNNs) with switching parameters and time delay. Quantized control is utilized to achieve the FTBS at a small control cost and with limited c...

TorchIO: A Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Processing of medical images such as MRI or CT presents different challenges compared to RGB images typically used in computer vision. These include a lack of labels for large datasets, high computational costs, and the need...

Automated cardiac segmentation of cross-modal medical images using unsupervised multi-domain adaptation and spatial neural attention structure.

Medical image analysis
Accurate cardiac segmentation of multimodal images, e.g., magnetic resonance (MR), computed tomography (CT) images, plays a pivot role in auxiliary diagnoses, treatments and postoperative assessments of cardiovascular diseases. However, training a we...

Development of Crime Scene Intelligence Using a Hand-Held Raman Spectrometer and Transfer Learning.

Analytical chemistry
The classification of ignitable liquids, such as gasoline, is critical crime scene intelligence to assist arson investigations. Rapid field gasoline classification is challenging because the current forensic testing standard requires gas chromatograp...

Open-Circuit Fault Detection and Classification of Modular Multilevel Converters in High Voltage Direct Current Systems (MMC-HVDC) with Long Short-Term Memory (LSTM) Method.

Sensors (Basel, Switzerland)
Fault detection and classification are two of the challenging tasks in Modular Multilevel Converters in High Voltage Direct Current (MMC-HVDC) systems. To directly classify the raw sensor data without certain feature extraction and classifier design,...