AIMC Topic: Algorithms

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Medical Image Captioning Using Optimized Deep Learning Model.

Computational intelligence and neuroscience
Medical image captioning provides the visual information of medical images in the form of natural language. It requires an efficient approach to understand and evaluate the similarity between visual and textual elements and to generate a sequence of ...

Machine Vision and Intelligent Algorithm Based on Neural Network.

Computational intelligence and neuroscience
Neural network algorithms and intelligent algorithms are hot topics in the field of deep learning. In this study, the neural network algorithm and intelligence are optimized, and it is used in simulation experiments to improve the target image recogn...

Compression of Deep Neural Networks based on quantized tensor decomposition to implement on reconfigurable hardware platforms.

Neural networks : the official journal of the International Neural Network Society
Deep Neural Networks (DNNs) have been vastly and successfully employed in various artificial intelligence and machine learning applications (e.g., image processing and natural language processing). As DNNs become deeper and enclose more filters per l...

Performance of the supervised learning algorithms in sex estimation of the proximal femur: A comparative study in contemporary Egyptian and Turkish samples.

Science & justice : journal of the Forensic Science Society
Sex estimation standards are population specific however, we argue that machine learning techniques (ML) may enhance the biological sex determination on trans-population application. Linear discriminant analysis (LDA) versus nine ML including quadrat...

[Low-field magnetic resonance imaging : Just less expensive or completely different?].

Der Radiologe
Over the years the development of field strength in magnetic resonance imaging (MRI) has continued to increase from the low-field systems in the early years (0.2-0.5 T) to 1.5 T to 3 T to 7 T and more. In the last 2 years, there has been a renewed in...

Machine Learning May Sometimes Simply Capture Literature Popularity Trends: A Case Study of Heterocyclic Suzuki-Miyaura Coupling.

Journal of the American Chemical Society
Applications of machine learning (ML) to synthetic chemistry rely on the assumption that large numbers of literature-reported examples should enable construction of accurate and predictive models of chemical reactivity. This paper demonstrates that a...

Introducing a Novel Model-Free Multivariable Adaptive Neural Network Controller for Square MIMO Systems.

Sensors (Basel, Switzerland)
In this study, a novel Multivariable Adaptive Neural Network Controller (MANNC) is developed for coupled model-free n-input n-output systems. The learning algorithm of the proposed controller does not rely on the model of a system and uses only the h...

Identification of Pharmacophoric Fragments of DYRK1A Inhibitors Using Machine Learning Classification Models.

Molecules (Basel, Switzerland)
Dual-specific tyrosine phosphorylation regulated kinase 1 (DYRK1A) has been regarded as a potential therapeutic target of neurodegenerative diseases, and considerable progress has been made in the discovery of DYRK1A inhibitors. Identification of pha...

An efficient self-attention network for skeleton-based action recognition.

Scientific reports
There has been significant progress in skeleton-based action recognition. Human skeleton can be naturally structured into graph, so graph convolution networks have become the most popular method in this task. Most of these state-of-the-art methods op...

Identifying key differences between linear stochastic estimation and neural networks for fluid flow regressions.

Scientific reports
Neural networks (NNs) and linear stochastic estimation (LSE) have widely been utilized as powerful tools for fluid-flow regressions. We investigate fundamental differences between them considering two canonical fluid-flow problems: (1) the estimation...