AIMC Topic: Attention

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An integrated framework for driving risk evaluation that combines lane-changing detection and an attention-based prediction model.

Traffic injury prevention
OBJECTIVE: In recent years, the increase in traffic accidents has emerged as a significant social issue that poses a serious threat to public safety. The objective of this study is to predict risky driving scenarios to improve road safety.

Predicting the effectiveness of binaural beats on working memory.

Neuroreport
Working memory is vital for short-term information processing. Binaural beats can enhance working memory by improving attention and memory consolidation through neural synchronization. However, individual differences in cognitive and neuronal functio...

Visual search and real-image similarity: An empirical assessment through the lens of deep learning.

Psychonomic bulletin & review
The ability to predict how efficiently a person finds an object in the environment is a crucial goal of attention research. Central to this issue are the similarity principles initially proposed by Duncan and Humphreys, which outline how the similari...

Early diagnosis of Alzheimer's Disease based on multi-attention mechanism.

PloS one
Alzheimer's Disease is a neurodegenerative disorder, and one of its common and prominent early symptoms is language impairment. Therefore, early diagnosis of Alzheimer's Disease through speech and text information is of significant importance. Howeve...

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...