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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...

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 ...

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...

3D-equivariant graph neural networks for protein model quality assessment.

Bioinformatics (Oxford, England)
MOTIVATION: Quality assessment (QA) of predicted protein tertiary structure models plays an important role in ranking and using them. With the recent development of deep learning end-to-end protein structure prediction techniques for generating highl...

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...

Protein model quality assessment using rotation-equivariant transformations on point clouds.

Proteins
Machine learning research concerning protein structure has seen a surge in popularity over the last years with promising advances for basic science and drug discovery. Working with macromolecular structure in a machine learning context requires an ad...

Shoulder Range of Motion Measurement Using Inertial Measurement Unit-Validation with a Robot Arm.

Sensors (Basel, Switzerland)
The invention of inertial measurement units allowed the construction of sensors suitable for human motion tracking that are more affordable than expensive optical motion capture systems, but there are a few factors influencing their accuracy, such as...

E(3) equivariant graph neural networks for robust and accurate protein-protein interaction site prediction.

PLoS computational biology
Artificial intelligence-powered protein structure prediction methods have led to a paradigm-shift in computational structural biology, yet contemporary approaches for predicting the interfacial residues (i.e., sites) of protein-protein interaction (P...

Understanding calibration of deep neural networks for medical image classification.

Computer methods and programs in biomedicine
Background and Objective - In the field of medical image analysis, achieving high accuracy is not enough; ensuring well-calibrated predictions is also crucial. Confidence scores of a deep neural network play a pivotal role in explainability by provid...