AIMC Topic: Neural Networks, Computer

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Quantum spin models for numerosity perception.

PloS one
Humans share with animals, both vertebrates and invertebrates, the capacity to sense the number of items in their environment already at birth. The pervasiveness of this skill across the animal kingdom suggests that it should emerge in very simple po...

FAST skill assessment from kinematics data using convolutional neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: FAST is a point of care ultrasound study that evaluates for the presence of free fluid, typically hemoperitoneum in trauma patients. FAST is an essential skill for Emergency Physicians. Thus, it requires objective evaluation tools that can r...

A multi-view co-training network for semi-supervised medical image-based prognostic prediction.

Neural networks : the official journal of the International Neural Network Society
Prognostic prediction has long been a hotspot in disease analysis and management, and the development of image-based prognostic prediction models has significant clinical implications for current personalized treatment strategies. The main challenge ...

Lifelong learning on evolving graphs under the constraints of imbalanced classes and new classes.

Neural networks : the official journal of the International Neural Network Society
Lifelong graph learning deals with the problem of continually adapting graph neural network (GNN) models to changes in evolving graphs. We address two critical challenges of lifelong graph learning in this work: dealing with new classes and tackling ...

Calibrating segmentation networks with margin-based label smoothing.

Medical image analysis
Despite the undeniable progress in visual recognition tasks fueled by deep neural networks, there exists recent evidence showing that these models are poorly calibrated, resulting in over-confident predictions. The standard practices of minimizing th...

Deep learning for classification of thyroid nodules on ultrasound: validation on an independent dataset.

Clinical imaging
OBJECTIVES: The purpose is to apply a previously validated deep learning algorithm to a new thyroid nodule ultrasound image dataset and compare its performances with radiologists.

Effective and efficient neural networks for spike inference from calcium imaging.

Cell reports methods
Calcium imaging provides advantages in monitoring large populations of neuronal activities simultaneously. However, it lacks the signal quality provided by neural spike recording in traditional electrophysiology. To address this issue, we developed a...

Computational complexity drives sustained deliberation.

Nature neuroscience
Economic deliberations are slow, effortful and intentional searches for solutions to difficult economic problems. Although such deliberations are critical for making sound decisions, the underlying reasoning strategies and neurobiological substrates ...

Microbiological Quality Estimation of Meat Using Deep CNNs on Embedded Hardware Systems.

Sensors (Basel, Switzerland)
Spectroscopic sensor imaging of food samples meta-processed by deep machine learning models can be used to assess the quality of the sample. This article presents an architecture for estimating microbial populations in meat samples using multispectra...

Algorithms and Techniques for the Structural Health Monitoring of Bridges: Systematic Literature Review.

Sensors (Basel, Switzerland)
Structural health monitoring (SHM) systems are used to analyze the health of infrastructures such as bridges, using data from various types of sensors. While SHM systems consist of various stages, feature extraction and pattern recognition steps are ...