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...
Analytical methods : advancing methods and applications
Sep 25, 2025
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...
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 ...
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 ...
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...
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,...
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...
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...
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...
Neural networks : the official journal of the International Neural Network Society
Jun 21, 2025
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...
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