AIMC Topic: Pattern Recognition, Automated

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A General DNA-Like Hybrid Symbiosis Framework: An EEG Cognitive Recognition Method.

IEEE journal of biomedical and health informatics
In electroencephalogram (EEG) cognitive recognition research, the combined use of artificial neural networks (ANNs) and spiking neural networks (SNNs) plays an important role to realize different categories of recognition tasks. However, most of the ...

Few-shot learning for inference in medical imaging with subspace feature representations.

PloS one
Unlike in the field of visual scene recognition, where tremendous advances have taken place due to the availability of very large datasets to train deep neural networks, inference from medical images is often hampered by the fact that only small amou...

Computer vision applications for the detection or analysis of tuberculosis using digitised human lung tissue images - a systematic review.

BMC medical imaging
OBJECTIVE: To conduct a systematic review of the computer vision applications that detect, diagnose, or analyse tuberculosis (TB) pathology or bacilli using digitised human lung tissue images either through automatic or semi-automatic methods. We cat...

Two-Stream Modality-Based Deep Learning Approach for Enhanced Two-Person Human Interaction Recognition in Videos.

Sensors (Basel, Switzerland)
Human interaction recognition (HIR) between two people in videos is a critical field in computer vision and pattern recognition, aimed at identifying and understanding human interaction and actions for applications such as healthcare, surveillance, a...

DiamondNet: A Neural-Network-Based Heterogeneous Sensor Attentive Fusion for Human Activity Recognition.

IEEE transactions on neural networks and learning systems
With the proliferation of intelligent sensors integrated into mobile devices, fine-grained human activity recognition (HAR) based on lightweight sensors has emerged as a useful tool for personalized applications. Although shallow and deep learning al...

A Static Sign Language Recognition Method Enhanced with Self-Attention Mechanisms.

Sensors (Basel, Switzerland)
For the current wearable devices in the application of cross-diversified user groups, it is common to face the technical difficulties of static sign language recognition accuracy attenuation, weak anti-noise ability, and insufficient system robustnes...

Open-set long-tailed recognition via orthogonal prototype learning and false rejection correction.

Neural networks : the official journal of the International Neural Network Society
Learning from data with long-tailed and open-ended distributions is highly challenging. In this work, we propose OLPR, which is a new dual-stream Open-set Long-tailed recognition framework based on orthogonal Prototype learning and false Rejection co...

Adapting Action Recognition Neural Networks for Automated Infantile Spasm Detection.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Infantile spasms are a severe epileptic syndrome characterized by short muscular contractions lasting from 0.5 to 2 seconds. They are often misdiagnosed due to their atypical presentation, and treatment is frequently delayed, leading to stagnation or...

Pattern recognition using spiking antiferromagnetic neurons.

Scientific reports
Spintronic devices offer a promising avenue for the development of nanoscale, energy-efficient artificial neurons for neuromorphic computing. It has previously been shown that with antiferromagnetic (AFM) oscillators, ultra-fast spiking artificial ne...

Hand gesture recognition using sEMG signals with a multi-stream time-varying feature enhancement approach.

Scientific reports
Hand gesture recognition based on sparse multichannel surface electromyography (sEMG) still poses a significant challenge to deployment as a muscle-computer interface. Many researchers have been working to develop an sEMG-based hand gesture recogniti...