AIMC Topic: Neural Networks, Computer

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Wafer-Scale 2D Hafnium Diselenide Based Memristor Crossbar Array for Energy-Efficient Neural Network Hardware.

Advanced materials (Deerfield Beach, Fla.)
Memristor crossbar with programmable conductance could overcome the energy consumption and speed limitations of neural networks when executing core computing tasks in image processing. However, the implementation of crossbar array (CBA) based on ultr...

A Bioinspired Stretchable Sensory-Neuromorphic System.

Advanced materials (Deerfield Beach, Fla.)
Conventional stretchable electronics that adopt a wavy design, a neutral mechanical plane, and conformal contact between abiotic and biotic interfaces have exhibited diverse skin-interfaced applications. Despite such remarkable progress, the evolutio...

Blood glucose concentration prediction based on VMD-KELM-AdaBoost.

Medical & biological engineering & computing
The time series of blood glucose concentration in diabetic patients are time-varying, nonlinear, and non-stationary. In order to improve the accuracy of blood glucose prediction, a multi-scale combination short-term blood glucose prediction model was...

Improved 3-D Protein Structure Predictions using Deep ResNet Model.

The protein journal
Protein Structure Prediction (PSP) is considered to be a complicated problem in computational biology. In spite of, the remarkable progress made by the co-evolution-based method in PSP, it is still a challenging and unresolved problem. Recently, alon...

Gap Reconstruction in Optical Motion Capture Sequences Using Neural Networks.

Sensors (Basel, Switzerland)
Optical motion capture is a mature contemporary technique for the acquisition of motion data; alas, it is non-error-free. Due to technical limitations and occlusions of markers, gaps might occur in such recordings. The article reviews various neural ...

Comparing Class-Aware and Pairwise Loss Functions for Deep Metric Learning in Wildlife Re-Identification.

Sensors (Basel, Switzerland)
Similarity learning using deep convolutional neural networks has been applied extensively in solving computer vision problems. This attraction is supported by its success in one-shot and zero-shot classification applications. The advances in similari...

Subgroup Preference Neural Network.

Sensors (Basel, Switzerland)
Subgroup label ranking aims to rank groups of labels using a single ranking model, is a new problem faced in preference learning. This paper introduces the Subgroup Preference Neural Network () that combines multiple networks have different activatio...

Mitigating Wireless Channel Impairments in Seismic Data Transmission Using Deep Neural Networks.

Sensors (Basel, Switzerland)
The traditional cable-based geophone network is an inefficient way of seismic data transmission owing to the related cost and weight. The future of oil and gas exploration technology demands large-scale seismic acquisition, versatility, flexibility, ...

Evaluating Deep Neural Network Architectures with Transfer Learning for Pneumonitis Diagnosis.

Computational and mathematical methods in medicine
Pneumonitis is an infectious disease that causes the inflammation of the air sac. It can be life-threatening to the very young and elderly. Detection of pneumonitis from X-ray images is a significant challenge. Early detection and assistance with dia...

Data-Driven Object Pose Estimation in a Practical Bin-Picking Application.

Sensors (Basel, Switzerland)
This paper addresses the problem of pose estimation from 2D images for textureless industrial metallic parts for a semistructured bin-picking task. The appearance of metallic reflective parts is highly dependent on the camera viewing direction, as we...