AIMC Topic: Algorithms

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A Reinforcement Learning-Based Strategy of Path Following for Snake Robots with an Onboard Camera.

Sensors (Basel, Switzerland)
For path following of snake robots, many model-based controllers have demonstrated strong tracking abilities. However, a satisfactory performance often relies on precise modelling and simplified assumptions. In addition, visual perception is also ess...

Proposal of a Real-Time Test Platform for Tactile Internet Systems.

Sensors (Basel, Switzerland)
This work aimed to develop a real-time test platform for systems associated with the tactile internet area. The proposal comprises a master device, a communication channel and a slave device. The master device is a tactile glove (wearable technology)...

Application for Recognizing Sign Language Gestures Based on an Artificial Neural Network.

Sensors (Basel, Switzerland)
This paper presents the development and implementation of an application that recognizes American Sign Language signs with the use of deep learning algorithms based on convolutional neural network architectures. The project implementation includes th...

Quantum variational algorithms are swamped with traps.

Nature communications
One of the most important properties of classical neural networks is how surprisingly trainable they are, though their training algorithms typically rely on optimizing complicated, nonconvex loss functions. Previous results have shown that unlike the...

Sparse inference and active learning of stochastic differential equations from data.

Scientific reports
Automatic machine learning of empirical models from experimental data has recently become possible as a result of increased availability of computational power and dedicated algorithms. Despite the successes of non-parametric inference and neural-net...

Physiological Status Prediction Based on a Novel Hybrid Intelligent Scheme.

Computational intelligence and neuroscience
Physiological status plays an important role in clinical diagnosis. However, the temporal physiological data change dynamically with time, and the amount of data is large; furthermore, obtaining a complete history of data has become difficult. We pro...

Computed Tomography slice interpolation in the longitudinal direction based on deep learning techniques: To reduce slice thickness or slice increment without dose increase.

PloS one
Large slice thickness or slice increment causes information insufficiency of Computed Tomography (CT) data in the longitudinal direction, which degrades the quality of CT-based diagnosis. Traditional approaches such as high-resolution computed tomogr...

A Brief Review of Artificial Intelligence in Genitourinary Oncological Imaging.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Genitourinary (GU) system is among the most commonly involved malignancy sites in the human body. Imaging plays a crucial role not only in diagnosis of cancer but also in disease management and its prognosis. However, interpretation of conventional i...

Operon Finder: A Deep Learning-based Web Server for Accurate Prediction of Prokaryotic Operons.

Journal of molecular biology
Operons are groups of consecutive genes that transcribe together under the regulation of a common promoter. They influence protein regulation and various physiological pathways, making their accurate detection desirable. The detection of operons thro...

U-SPDNet: An SPD manifold learning-based neural network for visual classification.

Neural networks : the official journal of the International Neural Network Society
With the development of neural networking techniques, several architectures for symmetric positive definite (SPD) matrix learning have recently been put forward in the computer vision and pattern recognition (CV&PR) community for mining fine-grained ...