AIMC Topic: Algorithms

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Human fall direction recognition in the indoor and outdoor environment using multi self-attention RBnet deep architectures and tree seed optimization.

Scientific reports
Falling poses a significant health risk to the elderly, often resulting in severe injuries if not promptly addressed. As the global population increases, the frequency of falls increases along with the associated financial burden. Hence, early detect...

Learning behavior aware features across spaces for improved 3D human motion prediction.

Scientific reports
3D skeleton-based human motion prediction is an essential and challenging task for human-machine interactions, aiming to forecast future poses given a history of previous motions. However, most existing works model human motion dependencies exclusive...

Semi-supervised contrastive learning variational autoencoder Integrating single-cell multimodal mosaic datasets.

BMC bioinformatics
As single-cell sequencing technology became widely used, scientists found that single-modality data alone could not fully meet the research needs of complex biological systems. To address this issue, researchers began simultaneously collect multi-mod...

A multisynaptic spiking neuron for simultaneously encoding spatiotemporal dynamics.

Nature communications
Spiking neural networks (SNNs) are biologically more plausible and computationally more powerful than artificial neural networks due to their intrinsic temporal dynamics. However, vanilla spiking neurons struggle to simultaneously encode spatiotempor...

Multi-scale feature pyramid network with bidirectional attention for efficient mural image classification.

PloS one
Mural image recognition plays a critical role in the digital preservation of cultural heritage; however, it faces cross-cultural and multi-period style generalization challenges, compounded by limited sample sizes and intricate details, such as losse...

Leveraging potential of limpid attention transformer with dynamic tokenization for hyperspectral image classification.

PloS one
Hyperspectral data consists of continuous narrow spectral bands. Due to this, it has less spatial and high spectral information. Convolutional neural networks (CNNs) emerge as a highly contextual information model for remote sensing applications. Unf...

Zero-shot performance analysis of large language models in sumrate maximization.

PloS one
Large language models have revolutionized the field of natural language processing and are now becoming a one-stop solution to various tasks. In the field of Networking, LLMs can also play a major role when it comes to resource optimization and shari...

Sentiment analysis for deepfake X posts using novel transfer learning based word embedding and hybrid LGR approach.

Scientific reports
With the growth of social media, people are sharing more content than ever, including X posts that reflect a variety of emotions and opinions. AI-generated synthetic text, known as deepfake text, is used to imitate human writing to disseminate mislea...

Cross-subject EEG signals-based emotion recognition using contrastive learning.

Scientific reports
Electroencephalography (EEG) signals based emotion brain computer interface (BCI) is a significant field in the domain of affective computing where EEG signals are the cause of reliable and objective applications. Despite these advancements, signific...

Adapting foundation models for rapid clinical response: intracerebral hemorrhage segmentation in emergency settings.

Scientific reports
Intracerebral hemorrhage (ICH) is a medical emergency that demands rapid and accurate diagnosis for optimal patient management. Hemorrhagic lesions' segmentation on CT scans is a necessary first step for acquiring quantitative imaging data that are b...