AIMC Topic: Humans

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Multiscale and Hierarchical Feature-Aggregation Network for Segmenting Medical Images.

Sensors (Basel, Switzerland)
We propose an encoder-decoder architecture using wide and deep convolutional layers combined with different aggregation modules for the segmentation of medical images. Initially, we obtain a rich representation of features that span from low to high ...

A Novel Transformer-Based Attention Network for Image Dehazing.

Sensors (Basel, Switzerland)
Image dehazing is challenging due to the problem of ill-posed parameter estimation. Numerous prior-based and learning-based methods have achieved great success. However, most learning-based methods use the changes and connections between scale and de...

Pattern Recognition of EMG Signals by Machine Learning for the Control of a Manipulator Robot.

Sensors (Basel, Switzerland)
Human Machine Interfaces (HMI) principles are for the development of interfaces for assistance or support systems in physiotherapy or rehabilitation processes. One of the main problems is the degree of customization when applying some rehabilitation ...

Identifying Blood Biomarkers for Dementia Using Machine Learning Methods in the Framingham Heart Study.

Cells
Blood biomarkers for dementia have the potential to identify preclinical disease and improve participant selection for clinical trials. Machine learning is an efficient analytical strategy to simultaneously identify multiple candidate biomarkers for ...

The efficacy of deep learning models in the diagnosis of endometrial cancer using MRI: a comparison with radiologists.

BMC medical imaging
PURPOSE: To compare the diagnostic performance of deep learning models using convolutional neural networks (CNN) with that of radiologists in diagnosing endometrial cancer and to verify suitable imaging conditions.

Da Vinci Robot-Assisted Video Image Processing under Artificial Intelligence Vision Processing Technology.

Computational and mathematical methods in medicine
This research was aimed to explore the application value of intelligent algorithm-based digital images in Da Vinci robot-assisted treatment of patients with gastric cancer surgery. 154 patients were included as the research objects, with 89 cases in ...

Hypertuned Deep Convolutional Neural Network for Sign Language Recognition.

Computational intelligence and neuroscience
Sign language plays a pivotal role in the lives of impaired people having speaking and hearing disabilities. They can convey messages using hand gesture movements. American Sign Language (ASL) recognition is challenging due to the increasing intra-cl...

Computer Vision-Based Medical Cloud Data System for Back Muscle Image Detection.

Computational intelligence and neuroscience
The fast development of image recognition and information technology has influenced people's life and industry management mode not only in some common fields such as information management, but also has very much improved the working efficiency of va...

Detection of Dental Diseases through X-Ray Images Using Neural Search Architecture Network.

Computational intelligence and neuroscience
An important aspect of the diagnosis procedure in daily clinical practice is the analysis of dental radiographs. This is because the dentist must interpret different types of problems related to teeth, including the tooth numbers and related diseases...

Online Anomaly Detection of Industrial IoT Based on Hybrid Machine Learning Architecture.

Computational intelligence and neuroscience
Industrial IoT (IIoT) in Industry 4.0 integrates everything at the level of information technology with the level of technology of operation and aims to improve Business to Business (B2B) services (from production to public services). It includes Mac...