AIMC Topic: Neural Networks, Computer

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NerveStitcher: Corneal confocal microscope images stitching with neural networks.

Computers in biology and medicine
Corneal nerves are of great interest to clinicians and scientists due to their potential for the diagnosis of early neurological disorders. In vivo confocal microscopy (IVCM) has been used as a novel and reliable tool for observing and quantifying co...

Experiments on Adversarial Examples for Deep Learning Model Using Multimodal Sensors.

Sensors (Basel, Switzerland)
Recently, artificial intelligence (AI) based on IoT sensors has been widely used, which has increased the risk of attacks targeting AI. Adversarial examples are among the most serious types of attacks in which the attacker designs inputs that can cau...

Deep learning-based framework for slide-based histopathological image analysis.

Scientific reports
Digital pathology coupled with advanced machine learning (e.g., deep learning) has been changing the paradigm of whole-slide histopathological images (WSIs) analysis. Major applications in digital pathology using machine learning include automatic ca...

Scalable graph neural network for NMR chemical shift prediction.

Physical chemistry chemical physics : PCCP
Graph neural networks (GNNs) have been proven effective in the fast and accurate prediction of nuclear magnetic resonance (NMR) chemical shifts of a molecule. Existing methods, despite their effectiveness, suffer from high space complexity and are th...

Dark-Channel Enhanced-Compensation Net: An end-to-end inner-reflection compensation method for immersive projection system.

PloS one
Immersive projection display system is widely adopted in virtual reality and various exhibition halls. How to maintain high display quality in an immersive projection environment with uneven illumination and the color deviation caused by the inter-re...

SENSDeep: An Ensemble Deep Learning Method for Protein-Protein Interaction Sites Prediction.

Interdisciplinary sciences, computational life sciences
PURPOSE: The determination of which amino acid in a protein interacts with other proteins is important in understanding the functional mechanism of that protein. Although there are experimental methods to detect protein-protein interaction sites (PPI...

Motion grading of high-resolution quantitative computed tomography supported by deep convolutional neural networks.

Bone
Image quality degradation due to subject motion confounds the precision and reproducibility of measurements of bone density, morphology and mechanical properties from high-resolution peripheral quantitative computed tomography (HR-pQCT). Time-consumi...

Druggable protein prediction using a multi-canal deep convolutional neural network based on autocovariance method.

Computers in biology and medicine
Drug targets must be identified and positioned correctly to research and manufacture new drugs. In this study, rather than using traditional methods for drug expansion, the drug target is determined using machine learning. Machine learning has genera...

Development of Liquid Chromatographic Retention Index Based on Cocamide Diethanolamine Homologous Series (C()-DEA).

Analytical chemistry
There is a growing need for indexing and harmonizing retention time (tR) data in liquid chromatography derived under different conditions to aid in the identification of compounds in high resolution mass spectrometry (HRMS) based suspect and nontarge...

Automatic Behavior Assessment from Uncontrolled Everyday Audio Recordings by Deep Learning.

Sensors (Basel, Switzerland)
The manual categorization of behavior from sensory observation data to facilitate further analyses is a very expensive process. To overcome the inherent subjectivity of this process, typically, multiple domain experts are involved, resulting in incre...