AIMC Topic: Rotation

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Fiber Bundle Image Reconstruction Using Convolutional Neural Networks and Bundle Rotation in Endomicroscopy.

Sensors (Basel, Switzerland)
Fiber-bundle endomicroscopy has several recognized drawbacks, the most prominent being the honeycomb effect. We developed a multi-frame super-resolution algorithm exploiting bundle rotation to extract features and reconstruct underlying tissue. Simul...

A Novel Tactile Function Assessment Using a Miniature Tactile Stimulator.

Sensors (Basel, Switzerland)
Several methods for the measurement of tactile acuity have been devised previously, but unexpected nonspatial cues and intensive manual skill requirements compromise measurement accuracy. Therefore, we must urgently develop an automated, accurate, an...

Continual learning with attentive recurrent neural networks for temporal data classification.

Neural networks : the official journal of the International Neural Network Society
Continual learning is an emerging research branch of deep learning, which aims to learn a model for a series of tasks continually without forgetting knowledge obtained from previous tasks. Despite receiving a lot of attention in the research communit...

Accuracy evaluation of hand-eye calibration techniques for vision-guided robots.

PloS one
Hand-eye calibration is an important step in controlling a vision-guided robot in applications like part assembly, bin picking and inspection operations etc. Many methods for estimating hand-eye transformations have been proposed in literature with v...

Technical note: A method to synthesize magnetic resonance images in different patient rotation angles with deep learning for gantry-free radiotherapy.

Medical physics
BACKGROUND: Recently, patient rotating devices for gantry-free radiotherapy, a new approach to implement external beam radiotherapy, have been introduced. When a patient is rotated in the horizontal position, gravity causes anatomic deformation. For ...

3DMol-Net: Learn 3D Molecular Representation Using Adaptive Graph Convolutional Network Based on Rotation Invariance.

IEEE journal of biomedical and health informatics
Studying the deep learning-based molecular representation has great significance on predicting molecular property, promoted the development of drug screening and new drug discovery, and improving human well-being for avoiding illnesses. It is essenti...

Design, development and evaluation of an ergonomically designed dual-use mechanism for robot-assisted cardiovascular intervention.

International journal of computer assisted radiology and surgery
PURPOSE: Robot-assisted cardiovascular intervention has been recently developed, which enables interventionists to avoid x-ray radiation and improve their comfort. However, there are still some challenges in the robotic design, such as the inability ...

An Improved Deep Residual Convolutional Neural Network for Plant Leaf Disease Detection.

Computational intelligence and neuroscience
In this research, we proposed a novel deep residual convolutional neural network with 197 layers (ResNet197) for the detection of various plant leaf diseases. Six blocks of layers were used to develop ResNet197. ResNet197 was trained and tested using...

Interactive and synergistic behaviours of multiple heterogeneous microrobots.

Lab on a chip
Microrobots have been extensively studied for biomedical applications, and significant innovations and advances have been made in diverse aspects of the field. However, most studies have been based on individual microrobots with limited capabilities,...

Oblique and rotation double random forest.

Neural networks : the official journal of the International Neural Network Society
Random Forest is an ensemble of decision trees based on the bagging and random subspace concepts. As suggested by Breiman, the strength of unstable learners and the diversity among them are the ensemble models' core strength. In this paper, we propos...