AIMC Topic: Neural Networks, Computer

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Deep learning and cognitive science.

Cognition
In recent years, the family of algorithms collected under the term "deep learning" has revolutionized artificial intelligence, enabling machines to reach human-like performances in many complex cognitive tasks. Although deep learning models are groun...

Appearance variation adaptation tracker using adversarial network.

Neural networks : the official journal of the International Neural Network Society
Visual trackers using deep neural networks have demonstrated favorable performance in object tracking. However, training a deep classification network using overlapped initial target regions may lead an overfitted model. To increase the model general...

Clinical questionnaire filling based on question answering framework.

International journal of medical informatics
BACKGROUND: Electronic Health Records (EHR) are the foundation of much medical research. However, analyzing the text data of EHRs directly is an challenging task. Therefore, physicians often use questionnaires to first convert text data to structured...

Prefrontal oscillations modulate the propagation of neuronal activity required for working memory.

Neurobiology of learning and memory
Cognition involves using attended information, maintained in working memory (WM), to guide action. During a cognitive task, a correct response requires flexible, selective gating so that only the appropriate information flows from WM to downstream ef...

Concept attribution: Explaining CNN decisions to physicians.

Computers in biology and medicine
Deep learning explainability is often reached by gradient-based approaches that attribute the network output to perturbations of the input pixels. However, the relevance of input pixels may be difficult to relate to relevant image features in some ap...

An Artificial Neural Network Assisted Dynamic Light Scattering Procedure for Assessing Living Cells Size in Suspension.

Sensors (Basel, Switzerland)
Dynamic light scattering (DLS) is an essential technique used for assessing the size of the particles in suspension, covering the range from nanometers to microns. Although it has been very well established for quite some time, improvement can still ...

Comparative study of artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and multiple linear regression (MLR) for modeling of Cu (II) adsorption from aqueous solution using biochar derived from rambutan (Nephelium lappaceum) peel.

Environmental monitoring and assessment
Presence of copper within water bodies deteriorates human health and degrades natural environment. This heavy metal in water is treated using a promising biochar derived from rambutan (Nephelium lappaceum) peel through slow pyrolysis. This research c...

Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population.

International immunopharmacology
Since December 2019 the novel coronavirus SARS-CoV-2 has been identified as the cause of the pandemic COVID-19. Early symptoms overlap with other common conditions such as common cold and Influenza, making early screening and diagnosis are crucial go...

A new Lyapunov functional for stability analysis of neutral-type Hopfield neural networks with multiple delays.

Neural networks : the official journal of the International Neural Network Society
This research paper conducts an investigation into the stability issue for a more general class of neutral-type Hopfield neural networks that involves multiple time delays in the states of neurons and multiple neutral delays in the time derivatives o...