AIMC Topic: Neural Networks, Computer

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Modeling Soil Temperature for Different Days Using Novel Quadruplet Loss-Guided LSTM.

Computational intelligence and neuroscience
Soil temperature ( ), a key variable in geosciences study, has generated growing interest among researchers. There are many factors affecting the spatiotemporal variation of , which poses immense challenges for the estimation. To enrich processi...

Deep learning approach based on superpixel segmentation assisted labeling for automatic pressure ulcer diagnosis.

PloS one
A pressure ulcer is an injury of the skin and underlying tissues adjacent to a bony eminence. Patients who suffer from this disease may have difficulty accessing medical care. Recently, the COVID-19 pandemic has exacerbated this situation. Automatic ...

Employing automatic content recognition for teaching methodology analysis in classroom videos.

PloS one
A teacher plays a pivotal role in grooming a society and paves way for its social and economic developments. Teaching is a dynamic role and demands continuous adaptation. A teacher adopts teaching techniques suitable for a certain discipline and a si...

Reconstruction of a Fully Paralleled Auditory Spiking Neural Network and FPGA Implementation.

IEEE transactions on biomedical circuits and systems
This paper presents a field-programmable gate array (FPGA) implementation of an auditory system, which is biologically inspired and has the advantages of robustness and anti-noise ability. We propose an FPGA implementation of an eleven-channel hierar...

Flexible Neural Network Realized by the Probabilistic SiO Memristive Synaptic Array for Energy-Efficient Image Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
The human brain's neural networks are sparsely connected via tunable and probabilistic synapses, which may be essential for performing energy-efficient cognitive and intellectual functions. In this sense, the implementation of a flexible neural netwo...

Residue-Frustration-Based Prediction of Protein-Protein Interactions Using Machine Learning.

The journal of physical chemistry. B
The study of protein-protein interactions (PPIs) is important in understanding the function of proteins. However, it is still a challenge to investigate the transient protein-protein interaction by experiments. Hence, the computational prediction for...

Structure-aware siamese graph neural networks for encounter-level patient similarity learning.

Journal of biomedical informatics
Patient similarity learning has attracted great research interest in biomedical informatics. Correctly identifying the similarity between a given patient and patient records in the database could contribute to clinical references for diagnosis and me...

Predicting machine's performance record using the stacked long short-term memory (LSTM) neural networks.

Journal of applied clinical medical physics
PURPOSE: The record of daily quality control (QC) items shows machine performance patterns and potentially provides warning messages for preventive actions. This study developed a neural network model that could predict the record and trend of data v...

Improved Position Estimation Algorithm of Agricultural Mobile Robots Based on Multisensor Fusion and Autoencoder Neural Network.

Sensors (Basel, Switzerland)
High-precision position estimations of agricultural mobile robots (AMRs) are crucial for implementing control instructions. Although the global navigation satellite system (GNSS) and real-time kinematic GNSS (RTK-GNSS) provide high-precision position...

Improving Radar Human Activity Classification Using Synthetic Data with Image Transformation.

Sensors (Basel, Switzerland)
Machine Learning (ML) methods have become state of the art in radar signal processing, particularly for classification tasks (e.g., of different human activities). Radar classification can be tedious to implement, though, due to the limited size and ...