AIMC Topic: Calibration

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Measuring haemolysis in cattle serum by direct UV-VIS and RGB digital image-based methods.

Scientific reports
A simple, rapid procedure is required for the routine detection and quantification of haemolysis, one of the main sources of unreliable results in serum analysis. In this study, we compared two different approaches for the rapid determination of haem...

Dynamically Weighted Balanced Loss: Class Imbalanced Learning and Confidence Calibration of Deep Neural Networks.

IEEE transactions on neural networks and learning systems
Imbalanced class distribution is an inherent problem in many real-world classification tasks where the minority class is the class of interest. Many conventional statistical and machine learning classification algorithms are subject to frequency bias...

Affordable Motion Tracking System for Intuitive Programming of Industrial Robots.

Sensors (Basel, Switzerland)
The paper deals with a lead-through method of programming for industrial robots. The goal is to automatically reproduce 6DoF trajectories of a tool wielded by a human operator demonstrating a motion task. We present a novel motion-tracking system bui...

Evaluation of artificial neural network designs for Gafchromicâ„¢ film calibration with Tc-99m and digital photos.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine

Deep Learning Framework for Integrating Multibatch Calibration, Classification, and Pathway Activities.

Analytical chemistry
The amount of available biological data has exploded since the emergence of high-throughput technologies, which is not only revolting the way we recognize molecules and diseases but also bringing novel analytical challenges to bioinformatics analysis...

Research on the Industrial Robot Grasping Method Based on Multisensor Data Fusion and Binocular Vision.

Computational intelligence and neuroscience
At present, most of the handling industrial robots working on the production line are operated by teaching or preprogramming, which makes the flexibility of the production line poor and does not meet the flexible production requirements of the materi...

Studying and mitigating the effects of data drifts on ML model performance at the example of chemical toxicity data.

Scientific reports
Machine learning models are widely applied to predict molecular properties or the biological activity of small molecules on a specific protein. Models can be integrated in a conformal prediction (CP) framework which adds a calibration step to estimat...

DGCyTOF: Deep learning with graphic cluster visualization to predict cell types of single cell mass cytometry data.

PLoS computational biology
Single-cell mass cytometry, also known as cytometry by time of flight (CyTOF) is a powerful high-throughput technology that allows analysis of up to 50 protein markers per cell for the quantification and classification of single cells. Traditional ma...

Transferability of multivariate extreme value models for safety assessment by applying artificial intelligence-based video analytics.

Accident; analysis and prevention
Traffic conflict techniques represent the state-of-the-art for road safety assessments. However, the lack of research on transferability of conflict-based crash risk models, which refers to applying the developed crash risk estimation models to a set...

Quantitative analysis of Raman spectra for glucose concentration in human blood using Gramian angular field and convolutional neural network.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this study, convolutional neural network based on Gramian angular field (GAF-CNN) was firstly proposed. The 1-D Raman spectral data was converted into images and used for predicting the biochemical value of blood glucose. 106 sets of blood spectru...