AIMC Topic: Automation

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Programming Robots by Demonstration Using Augmented Reality.

Sensors (Basel, Switzerland)
The world is living the fourth industrial revolution, marked by the increasing intelligence and automation of manufacturing systems. Nevertheless, there are types of tasks that are too complex or too expensive to be fully automated, it would be more ...

DEEP picker is a deep neural network for accurate deconvolution of complex two-dimensional NMR spectra.

Nature communications
The analysis of nuclear magnetic resonance (NMR) spectra for the comprehensive and unambiguous identification and characterization of peaks is a difficult, but critically important step in all NMR analyses of complex biological molecular systems. Her...

A deep learning approach to automatic gingivitis screening based on classification and localization in RGB photos.

Scientific reports
Routine dental visit is the most common approach to detect the gingivitis. However, such diagnosis can sometimes be unavailable due to the limited medical resources in certain areas and costly for low-income populations. This study proposes to screen...

Multi-muscle deep learning segmentation to automate the quantification of muscle fat infiltration in cervical spine conditions.

Scientific reports
Muscle fat infiltration (MFI) has been widely reported across cervical spine disorders. The quantification of MFI requires time-consuming and rater-dependent manual segmentation techniques. A convolutional neural network (CNN) model was trained to se...

Automated Bowel Sound Analysis: An Overview.

Sensors (Basel, Switzerland)
Despite technological progress, we lack a consensus on the method of conducting automated bowel sound (BS) analysis and, consequently, BS tools have not become available to doctors. We aimed to briefly review the literature on BS recording and analys...

The Role of Artificial Intelligence and Machine Learning in Clinical Cardiac Electrophysiology.

The Canadian journal of cardiology
In recent years, numerous applications for artificial intelligence (AI) in cardiology have been found, due in part to large digitized data sets and the evolution of high-performance computing. In the discipline of cardiac electrophysiology (EP), a nu...

Towards Lifespan Automation for Based on Deep Learning: Analysing Convolutional and Recurrent Neural Networks for Dead or Live Classification.

Sensors (Basel, Switzerland)
The automation of lifespan assays with in standard Petri dishes is a challenging problem because there are several problems hindering detection such as occlusions at the plate edges, dirt accumulation, and worm aggregations. Moreover, determining wh...

A systematic review of machine learning and automation in burn wound evaluation: A promising but developing frontier.

Burns : journal of the International Society for Burn Injuries
BACKGROUND: Visual evaluation is the most common method of evaluating burn wounds. Its subjective nature can lead to inaccurate diagnoses and inappropriate burn center referrals. Machine learning may provide an objective solution. The objective of th...

Deep Learning for Basal Cell Carcinoma Detection for Reflectance Confocal Microscopy.

The Journal of investigative dermatology
Basal cell carcinoma (BCC) is the most common skin cancer, with over 2 million cases diagnosed annually in the United States. Conventionally, BCC is diagnosed by naked eye examination and dermoscopy. Suspicious lesions are either removed or biopsied ...

Automation Pyramid as Constructor for a Complete Digital Twin, Case Study: A Didactic Manufacturing System.

Sensors (Basel, Switzerland)
Nowadays, the concept of Industry 4.0 aims to improve factories' competitiveness. Usually, manufacturing production is guided by standards to segment and distribute its processes and implementations. However, industry 4.0 requires innovative proposal...