AIMC Topic: Neural Networks, Computer

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Skeleton-Based Abnormal Behavior Detection Using Secure Partitioned Convolutional Neural Network Model.

IEEE journal of biomedical and health informatics
Theabnormal behavior detection is the vital for evaluation of daily-life health status of the patient with cognitive impairment. Previous studies about abnormal behavior detection indicate that convolution neural network (CNN)-based computer vision o...

Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation.

Journal of digital imaging
The Dice similarity coefficient (DSC) is both a widely used metric and loss function for biomedical image segmentation due to its robustness to class imbalance. However, it is well known that the DSC loss is poorly calibrated, resulting in overconfid...

Deep convolutional neural network with sine cosine algorithm based wastewater treatment systems.

Environmental research
Wastewater treatment systems are essential in today's business to meet the ever-increasing requirements of environmental regulations while also limiting the environmental impact of the sector's discharges. A new control and management information sys...

Estimations for (n,α) reaction cross sections at around 14.5MeV using Levenberg-Marquardt algorithm-based artificial neural network.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
Prediction of neutron-induced reaction cross-sections at around the 14.5 MeV neutron energy is crucial to calculate nuclear transmutation rates, nuclear heating, and radiation damage from gas formation in fusion reactor technology In this research, t...

Global stability of a continuous bioreactor model under persistent variation of the dilution rate.

Mathematical biosciences and engineering : MBE
In this work, the global stability of a continuous bioreactor model is studied, with the concentrations of biomass and substrate as state variables, a general non-monotonic function of substrate concentration for the specific growth rate, and constan...

Compact Wideband Double-Slot Microstrip Feed Engraved TEM Horn Strip Antennas on a Multilayer Substrate Board for in Bed Resting Body Positions Determination Based on Artificial Intelligence.

Sensors (Basel, Switzerland)
In this paper, a horn-shaped strip antenna exponentially tapered carved on a multilayer dielectric substrate for an indoor body position tracking system is proposed. The performance of the proposed antenna was verified by testing it as a tracking sta...

Image Classification Using Multiple Convolutional Neural Networks on the Fashion-MNIST Dataset.

Sensors (Basel, Switzerland)
As the elderly population grows, there is a need for caregivers, which may become unsustainable for society. In this situation, the demand for automated help increases. One of the solutions is service robotics, in which robots have automation and sho...

Improved CNN-Based Indoor Localization by Using RGB Images and DBSCAN Algorithm.

Sensors (Basel, Switzerland)
With the intense deployment of wireless systems and the widespread use of intelligent equipment, the requirement for indoor positioning services is increasing, and Wi-Fi fingerprinting has emerged as the most often used approach to identifying indoor...

The Short-Term Prediction of Length of Day Using 1D Convolutional Neural Networks (1D CNN).

Sensors (Basel, Switzerland)
Accurate Earth orientation parameter (EOP) predictions are needed for many applications, e.g., for the tracking and navigation of interplanetary spacecraft missions. One of the most difficult parameters to forecast is the length of day (LOD), which r...

Machine learning-based predictions of gamma passing rates for virtual specific-plan verification based on modulation maps, monitor unit profiles, and composite dose images.

Physics in medicine and biology
Machine learning (ML) methods have been implemented in radiotherapy to aid virtual specific-plan verification protocols, predicting gamma passing rates (GPR) based on calculated modulation complexity metrics because of their direct relation to dose d...