AIMC Topic: Neural Networks, Computer

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BACPI: a bi-directional attention neural network for compound-protein interaction and binding affinity prediction.

Bioinformatics (Oxford, England)
MOTIVATION: The identification of compound-protein interactions (CPIs) is an essential step in the process of drug discovery. The experimental determination of CPIs is known for a large amount of funds and time it consumes. Computational model has th...

Convolutional Neural Network-Based Computer-Assisted Diagnosis of Hashimoto's Thyroiditis on Ultrasound.

The Journal of clinical endocrinology and metabolism
PURPOSE: This study investigates the efficiency of deep learning models in the automated diagnosis of Hashimoto's thyroiditis (HT) using real-world ultrasound data from ultrasound examinations by computer-assisted diagnosis (CAD) with artificial inte...

Comparison of the Representational Power of Random Forests, Binary Decision Diagrams, and Neural Networks.

Neural computation
In this letter, we compare the representational power of random forests, binary decision diagrams (BDDs), and neural networks in terms of the number of nodes. We assume that an axis-aligned function on a single variable is assigned to each edge in ra...

Understanding Dynamics of Nonlinear Representation Learning and Its Application.

Neural computation
Representations of the world environment play a crucial role in artificial intelligence. It is often inefficient to conduct reasoning and inference directly in the space of raw sensory representations, such as pixel values of images. Representation l...

Adaptive Learning Neural Network Method for Solving Time-Fractional Diffusion Equations.

Neural computation
A neural network method for solving fractional diffusion equations is presented in this letter. An adaptive gradient descent method is proposed to minimize energy functions. Due to the memory effects of the fractional calculus, the gradient of energy...

TF-Unet:An automatic cardiac MRI image segmentation method.

Mathematical biosciences and engineering : MBE
Personalized heart models are widely used to study the mechanisms of cardiac arrhythmias and have been used to guide clinical ablation of different types of arrhythmias in recent years. MRI images are now mostly used for model building. In cardiac mo...

Knowledge distillation circumvents nonlinearity for optical convolutional neural networks.

Applied optics
In recent years, convolutional neural networks (CNNs) have enabled ubiquitous image processing applications. As such, CNNs require fast forward propagation runtime to process high-resolution visual streams in real time. This is still a challenging ta...

Learning spectral initialization for phase retrieval via deep neural networks.

Applied optics
Phase retrieval (PR) arises from the lack of phase information in the measures recorded by optical sensors. Phase masks that modulate the optical field and reduce ambiguities in the PR problem by producing redundancy in coded diffraction patterns (CD...

Neural-network-based method for improving measurement accuracy of four-quadrant detectors.

Applied optics
Due to the high accuracy and fast response, measurement systems based on four-quadrant detectors (4QDs) are widely used. There is a non-linear relationship between the output signal offset (OSO) of the 4QD and the actual spot position, resulting in l...

CapsNet-COVID19: Lung CT image classification method based on CapsNet model.

Mathematical biosciences and engineering : MBE
The outbreak of the Corona Virus Disease 2019 (COVID-19) has posed a serious threat to human health and life around the world. As the number of COVID-19 cases continues to increase, many countries are facing problems such as errors in nucleic acid te...