AIMC Topic: Pattern Recognition, Automated

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Advanced gesture recognition in Indian sign language using a synergistic combination of YOLOv10 with Swin Transformer model.

Scientific reports
Communication between deaf or mute individuals and hearing persons is often hindered by the lack of mutual understanding of sign or vocal language. To bridge this gap, Indian Sign Language Recognition (ISLR) systems are essential. This paper proposes...

Machine learning-powered plasmonic pattern recognition: etch-suppressed gold nanorods for multiplex urinary analysis of catecholamine neurotransmitters.

Analytical methods : advancing methods and applications
Simultaneous monitoring of catecholamine neurotransmitters (CNTs)-including epinephrine (Epi), norepinephrine (NE), levodopa (L-DOPA), and dopamine (DA)-is essential for the accurate diagnosis and effective management of various neurological disorder...

Water meter reading recognition method based on character attention mechanism.

PloS one
With the rapid advancement of computer vision technology, traditional manual methods of reading meters are increasingly being replaced by automated water meter reading technologies based on image recognition. This technology can precisely locate and ...

Enhancing surface electromyographic signal recognition accuracy for trans-radial amputees using broad learning systems.

Biomedical physics & engineering express
Gesture recognition based on surface electromyography (sEMG) plays a crucial role in human-computer interaction. By analyzing sEMG signals generated from residual forearm muscle activity in trans-radial amputees, it is possible to predict their hand ...

Discriminative graph regularized representation learning for recognition.

PloS one
Feature extraction has been extensively studied in the machine learning field as it plays a critical role in the success of various practical applications. To uncover compact low-dimensional feature representations with strong generalization and disc...

Video swin-CLSTM transformer: Enhancing human action recognition with optical flow and long-term dependencies.

PloS one
As video data volumes soar exponentially, the significance of video content analysis, particularly Human Action Recognition (HAR), has become increasingly prominent in fields such as intelligent surveillance, sports analytics, medical rehabilitation,...

An improved lightweight method based on EfficientNet for birdsong recognition.

Scientific reports
In the context of birdsong recognition, conventional modeling approaches often involve a significant number of parameters and high computational costs, rendering them unsuitable for deployment in embedded field monitoring devices. To improve the conv...

Enhancing occluded and standard bird object recognition using fuzzy-based ensembled computer vision approach with convolutional neural network.

Scientific reports
Classifying bird species is essential for ecological study and biodiversity protection, currently, conventional approaches are frequently laborious and susceptible to mistakes. Convolutional Neural Networks (CNNs) provide a more reliable option for f...

A flow pattern recognition method for gas-liquid two-phase flow based on dilated convolutional channel attention mechanism.

PloS one
Addressing the issue of insufficient key feature extraction leading to low recognition rates in existing deep learning-based flow pattern identification methods, this paper proposes a novel flow pattern image recognition model, Enhanced DenseNet with...

Learning multi-regularized mutation-aware correlation filter for object tracking via an adaptive hybrid model.

Neural networks : the official journal of the International Neural Network Society
Discriminative Correlation Filters (DCF) have emerged as a popular and effective approach in object tracking. With promising performance and efficiency, DCF-based trackers achieved impressive attention and reliable tracking results in several challen...