AIMC Topic: Pattern Recognition, Automated

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A strategy based on paraconsistent random forest for sEMG gesture recognition systems robust to contaminated data.

Computers in biology and medicine
Applying machine learning algorithms to physical signals is always challenging since undesirable events can occur when signals are acquired outside a controlled environment. Among several applications, movement recognition through sEMG signals is esp...

A method for feature division of Soccer Foul actions based on salience image semantics.

PloS one
The purpose of this study is to realize the automatic identification and classification of fouls in football matches and improve the overall identification accuracy. Therefore, a Deep Learning-Based Saliency Prediction Model (DLSPM) is proposed. DLSP...

Evaluating large language models for information extraction from gastroscopy and colonoscopy reports through multi-strategy prompting.

Journal of biomedical informatics
OBJECTIVE: To systematically evaluate large language models (LLMs) for automated information extraction from gastroscopy and colonoscopy reports through prompt engineering, addressing their ability to extract structured information, recognize complex...

An improved Red-billed blue magpie feature selection algorithm for medical data processing.

PloS one
Feature selection is a crucial preprocessing step in the fields of machine learning, data mining and pattern recognition. In medical data analysis, the large number and complexity of features are often accompanied by redundant or irrelevant features,...

EFCRFNet: A novel multi-scale framework for salient object detection.

PloS one
Salient Object Detection (SOD) is a fundamental task in computer vision, aiming to identify prominent regions within images. Traditional methods and deep learning-based models often encounter challenges in capturing crucial information in complex sce...

3D Micro-Expression Recognition Based on Adaptive Dynamic Vision.

Sensors (Basel, Switzerland)
In the research on intelligent perception, dynamic emotion recognition has been the focus in recent years. Small samples and unbalanced data are the main reasons for the low recognition accuracy of current technologies. Inspired by circular convoluti...

SAMSnake: A generic contour-based instance segmentation network assisted by Efficient Segment Anything Model.

Neural networks : the official journal of the International Neural Network Society
Contour-based instance segmentation has gained significant attention due to its efficiency and ability to produce precise segmentation boundaries. In this paper, we propose SAMSnake, a novel contour-based instance segmentation network. Our method int...

Multi-modal sentiment recognition with residual gating network and emotion intensity attention.

Neural networks : the official journal of the International Neural Network Society
Multimodal emotion recognition focuses on the prediction of emotions using text, visual and acoustic modalities, and some results have been generated in this field. Previous approaches fall short in two aspects, one is the processing of complementary...

A multi-filter deep transfer learning framework for image-based autism spectrum disorder detection.

Scientific reports
Autism Spectrum Disorder (ASD) affects approximately [Formula: see text] of the global population and is characterized by difficulties in social communication and repetitive or obsessive behaviors. Early detection of autism is crucial, as it allows t...

Intelligent recognition of human activities using deep learning techniques.

PloS one
Recognition of Human Actions (HAR) Portrays a crucial significance in various applications due to its ability for analyzing behaviour of humans within videos. This research investigates HAR in Red, Green, and Blue, or RGB videos using frameworks for ...