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OxcarNet: sinc convolutional network with temporal and channel attention for prediction of oxcarbazepine monotherapy responses in patients with newly diagnosed epilepsy.

Journal of neural engineering
Monotherapy with antiepileptic drugs (AEDs) is the preferred strategy for the initial treatment of epilepsy. However, an inadequate response to the initially prescribed AED is a significant indicator of a poor long-term prognosis, emphasizing the imp...

An attentional mechanism model for segmenting multiple lesion regions in the diabetic retina.

Scientific reports
Diabetic retinopathy (DR), a leading cause of blindness in diabetic patients, necessitates the precise segmentation of lesions for the effective grading of lesions. DR multi-lesion segmentation faces the main concerns as follows. On the one hand, ret...

Boosting cross-modal retrieval in remote sensing via a novel unified attention network.

Neural networks : the official journal of the International Neural Network Society
With the rapid advent and abundance of remote sensing data in different modalities, cross-modal retrieval tasks have gained importance in the research community. Cross-modal retrieval belongs to the research paradigm in which the query is of one moda...

Exploring refined dual visual features cross-combination for image captioning.

Neural networks : the official journal of the International Neural Network Society
For current image caption tasks used to encode region features and grid features Transformer-based encoders have become commonplace, because of their multi-head self-attention mechanism, the encoder can better capture the relationship between differe...

ABR-Attention: An Attention-Based Model for Precisely Localizing Auditory Brainstem Response.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Auditory Brainstem Response (ABR) is an evoked potential in the brainstem's neural centers in response to sound stimuli. Clinically, characteristic waves, especially Wave V latency, extracted from ABR can objectively indicate auditory loss and diagno...

A developmental model of audio-visual attention (MAVA) for bimodal language learning in infants and robots.

Scientific reports
A social individual needs to effectively manage the amount of complex information in his or her environment relative to his or her own purpose to obtain relevant information. This paper presents a neural architecture aiming to reproduce attention mec...

GlobalSR: Global context network for single image super-resolution via deformable convolution attention and fast Fourier convolution.

Neural networks : the official journal of the International Neural Network Society
Vision Transformer have achieved impressive performance in image super-resolution. However, they suffer from low inference speed mainly because of the quadratic complexity of multi-head self-attention (MHSA), which is the key to learning long-range d...

DualAttlog: Context aware dual attention networks for log-based anomaly detection.

Neural networks : the official journal of the International Neural Network Society
Most existing log-driven anomaly detection methods assume that logs are static and unchanged, which is often impractical. To address this, we propose a log anomaly detection model called DualAttlog. This model includes word-level and sequence-level s...

A Generalized Attention Mechanism to Enhance the Accuracy Performance of Neural Networks.

International journal of neural systems
In many modern machine learning (ML) models, attention mechanisms (AMs) play a crucial role in processing data and identifying significant parts of the inputs, whether these are text or images. This selective focus enables subsequent stages of the mo...

Integration of multi-level semantics in PTMs with an attention model for question matching.

PloS one
The task of question matching/retrieval focuses on determining whether two questions are semantically equivalent. It has garnered significant attention in the field of natural language processing (NLP) due to its commercial value. While neural networ...