AIMC Topic: Neural Networks, Computer

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Verte-Box: A Novel Convolutional Neural Network for Fully Automatic Segmentation of Vertebrae in CT Image.

Tomography (Ann Arbor, Mich.)
Due to the complex shape of the vertebrae and the background containing a lot of interference information, it is difficult to accurately segment the vertebrae from the computed tomography (CT) volume by manual segmentation. This paper proposes a conv...

Human Activity Recognition via Hybrid Deep Learning Based Model.

Sensors (Basel, Switzerland)
In recent years, Human Activity Recognition (HAR) has become one of the most important research topics in the domains of health and human-machine interaction. Many Artificial intelligence-based models are developed for activity recognition; however, ...

A Remote Calibration Device Using Edge Intelligence.

Sensors (Basel, Switzerland)
Power system facility calibration is a compulsory task that requires in-site operations. In this work, we propose a remote calibration device that incorporates edge intelligence so that the required calibration can be accomplished with little human i...

Evolved explainable classifications for lymph node metastases.

Neural networks : the official journal of the International Neural Network Society
A novel evolutionary approach for Explainable Artificial Intelligence is presented: the "Evolved Explanations" model (EvEx). This methodology combines Local Interpretable Model Agnostic Explanations (LIME) with Multi-Objective Genetic Algorithms to a...

An RNA-based theory of natural universal computation.

Journal of theoretical biology
Life is confronted with computation problems in a variety of domains including animal behavior, single-cell behavior, and embryonic development. Yet we currently do not know of a naturally existing biological system that is capable of universal compu...

Saliency map-guided hierarchical dense feature aggregation framework for breast lesion classification using ultrasound image.

Computer methods and programs in biomedicine
Deep learning methods, especially convolutional neural networks, have advanced the breast lesion classification task using breast ultrasound (BUS) images. However, constructing a highly-accurate classification model still remains challenging due to c...

Deep transfer learning based model for colorectal cancer histopathology segmentation: A comparative study of deep pre-trained models.

International journal of medical informatics
Colorectal cancer is one of the leading causes of cancer-related death, worldwide. Early detection of suspicious tissues can significantly improve the survival rate. In this study, the performance of a wide variety of deep learning-based architecture...

Use of the deep learning approach to measure alveolar bone level.

Journal of clinical periodontology
AIM: The goal was to use a deep convolutional neural network to measure the radiographic alveolar bone level to aid periodontal diagnosis.

Using Deep Learning to Automate the Detection of Flaws in Nuclear Fuel Channel UT Scans.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nuclear reactor inspections are critical to ensure the safety and reliability of a nuclear facility's operation. In Canada, ultrasonic testing (UT) is used to inspect the health of pressure tubes that are part of Canada's Deuterium Uranium (CANDU) re...

Sensor Data Fusion for a Mobile Robot Using Neural Networks.

Sensors (Basel, Switzerland)
Mobile robots must be capable to obtain an accurate map of their surroundings to move within it. To detect different materials that might be undetectable to one sensor but not others it is necessary to construct at least a two-sensor fusion scheme. W...