AIMC Topic: Attention

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Enhancing few-shot image classification through learnable multi-scale embedding and attention mechanisms.

Neural networks : the official journal of the International Neural Network Society
In the context of few-shot classification, the goal is to train a classifier using a limited number of samples while maintaining satisfactory performance. However, traditional metric-based methods exhibit certain limitations in achieving this objecti...

Attribute-guided feature fusion network with knowledge-inspired attention mechanism for multi-source remote sensing classification.

Neural networks : the official journal of the International Neural Network Society
Land use and land cover (LULC) classification is a popular research area in remote sensing. The information of single-modal data is insufficient for accurate classification, especially in complex scenes, while the complementarity of multi-modal data ...

CNNs improve decoding of selective attention to speech in cochlear implant users.

Journal of neural engineering
. Understanding speech in the presence of background noise such as other speech streams is a difficult problem for people with hearing impairment, and in particular for users of cochlear implants (CIs). To improve their listening experience, auditory...

Attention Regulation Among Sleep-Deprived Air-Force Pilots.

Journal of neuroscience research
Short sleep duration is associated with adverse physical and mental events. However, it is quite challenging to objectively quantify its impact on human cognitive performance. Thus, we aim to examine the effects of sleep deprivation on physiological ...

Reconstruction of highly and extremely aberrated wavefront for ocular Shack-Hartmann sensor using multi-task Attention-UNet.

Experimental eye research
In certain ocular conditions, such as in eyes with keratoconus or after corneal laser surgery, Higher Order Aberrations (HOAs) may be dramatically elevated. Accurately recording interpretable wavefronts in such highly aberrated eyes using Shack-Hartm...

Emotion-Aware RoBERTa enhanced with emotion-specific attention and TF-IDF gating for fine-grained emotion recognition.

Scientific reports
Emotion recognition in text is a fundamental task in natural language processing, underpinning applications such as sentiment analysis, mental health monitoring, and content moderation. Although transformer-based models like RoBERTa have advanced con...

Assessment of Driver Inattention State Using Multimodal Wearable Signals and Cross-Attention-Driven Hierarchical Fusion.

Studies in health technology and informatics
Identifying driver inattention is crucial for road safety, driver well-being and can be enhanced using multimodal physiological signals. However, effective fusion of multimodal data is highly challenging, particularly with intermediate fusion, where ...

g-Distance: On the comparison of model and human heterogeneity.

Psychological review
Models are often evaluated when their behavior is at its closest to a single, sometimes averaged, set of empirical results, but this evaluation neglects the fact that both model and human behavior can be heterogeneous. Here, we develop a measure, -di...

[Neural network for auditory speech enhancement featuring feedback-driven attention and lateral inhibition].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
The processing mechanism of the human brain for speech information is a significant source of inspiration for the study of speech enhancement technology. Attention and lateral inhibition are key mechanisms in auditory information processing that can ...

A robotics-inspired scanpath model reveals the importance of uncertainty and semantic object cues for gaze guidance in dynamic scenes.

Journal of vision
The objects we perceive guide our eye movements when observing real-world dynamic scenes. Yet, gaze shifts and selective attention are critical for perceiving details and refining object boundaries. Object segmentation and gaze behavior are, however,...