AIMC Topic: Neural Networks, Computer

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Generative Adversarial Networks for Morphological-Temporal Classification of Stem Cell Images.

Sensors (Basel, Switzerland)
Frequently, neural network training involving biological images suffers from a lack of data, resulting in inefficient network learning. This issue stems from limitations in terms of time, resources, and difficulty in cellular experimentation and data...

A High-Dimensional and Small-Sample Submersible Fault Detection Method Based on Feature Selection and Data Augmentation.

Sensors (Basel, Switzerland)
The fault detection of manned submersibles plays a very important role in protecting the safety of submersible equipment and personnel. However, the diving sensor data is scarce and high-dimensional, so this paper proposes a submersible fault detecti...

Brain CT registration using hybrid supervised convolutional neural network.

Biomedical engineering online
BACKGROUND: Image registration is an essential step in the automated interpretation of the brain computed tomography (CT) images of patients with acute cerebrovascular disease (ACVD). However, performing brain CT registration accurately and rapidly r...

Underwater gliders linear trajectory tracking: The experience breeding actor-critic approach.

ISA transactions
This paper studies the underwater glider trajectory tracking in currents field. The objective is to ensure that trajectories fit to the straight target track. The underwater glider model is introduced to demonstrate the vehicle dynamic properties. Co...

In vivo detection of head and neck tumors by hyperspectral imaging combined with deep learning methods.

Journal of biophotonics
Currently, there are no fast and accurate screening methods available for head and neck cancer, the eighth most common tumor entity. For this study, we used hyperspectral imaging, an imaging technique for quantitative and objective surface analysis, ...

Federated Learning for 5G Radio Spectrum Sensing.

Sensors (Basel, Switzerland)
Spectrum sensing (SS) is an important tool in finding new opportunities for spectrum sharing. The users, called Secondary Users (SU), who do not have a license to transmit without hindrance, need to employ SS in order to detect and use the spectrum w...

Fault Diagnosis of Rotating Machinery Based on Improved Self-Supervised Learning Method and Very Few Labeled Samples.

Sensors (Basel, Switzerland)
Convolution neural network (CNN)-based fault diagnosis methods have been widely adopted to obtain representative features and used to classify fault modes due to their prominent feature extraction capability. However, a large number of labeled sample...

Visual Perceptual Quality Assessment Based on Blind Machine Learning Techniques.

Sensors (Basel, Switzerland)
This paper presents the construction of a new objective method for estimation of visual perceiving quality. The proposal provides an assessment of image quality without the need for a reference image or a specific distortion assumption. Two main proc...

Robust Human Activity Recognition by Integrating Image and Accelerometer Sensor Data Using Deep Fusion Network.

Sensors (Basel, Switzerland)
Studies on deep-learning-based behavioral pattern recognition have recently received considerable attention. However, if there are insufficient data and the activity to be identified is changed, a robust deep learning model cannot be created. This wo...

Deep Learning Approach at the Edge to Detect Iron Ore Type.

Sensors (Basel, Switzerland)
There is a constant risk of iron ore collapsing during its transfer between processing stages in beneficiation plants. Existing instrumentation is not only expensive but also complex and challenging to maintain. In this research, we propose using edg...