Topic
Focusing attention
About: Focusing attention is a research topic. Over the lifetime, 90 publications have been published within this topic receiving 4360 citations.
Papers published on a yearly basis
Papers
TL;DR: Information-processing research provides an important viewpoint from which to understand the group of schizophrenias and recent advances and novel applications of these techniques in "boundary" populations such as high-risk children and schizotypal patients are discussed.
Abstract: Abnormalities of information processing have played a central role in understanding schizophrenia since the time of Kraepelin and Bleuler. Clearly, schizophrenia spectrum patients have profound problems focusing attention on salient cues and overcoming the disrupting effects of distracting stimuli. Theoretically, such patients are rendered vulnerable to stimulus inundation, cognitive fragmentation, and thought disorder induced by this inability to adequately process self-generated cognitive cues and stimuli from the complex world that surrounds us. Adding to the strength of such theories, investigators have made considerable progress in clarifying the functional significance and neurobiological basis of information-processing/attentional dysfunctions. This article focuses on our understanding of information-processing/attentional dysfunctions in schizophrenia. The relevant material will be presented in four parts: (1) an overview; (2) a review of specific, conceptual issues in information-processing research of the group of schizophrenias, including the roles of antipsychotic medications and generalized versus specific deficits; (3) a review of 10 common techniques used to tap the information processing and attention dysfunctions of schizophrenia patients; recent advances and novel applications of these techniques in "boundary" populations such as high-risk children and schizotypal patients are discussed and psychopharmacological probes, animal models, and basic strategies are also reviewed; and (4) an integration and suggestions for future directions in information-processing/attention research in schizophrenia. Overall, information-processing research provides an important viewpoint from which we can understand the group of schizophrenias.
789 citations
TL;DR: Focusing Attention Network (FAN) as discussed by the authors employs a focusing attention mechanism to automatically draw back the attention drift in the encoder-decoder framework, which is the state-of-the-art for scene text recognition.
Abstract: Scene text recognition has been a hot research topic in computer vision due to its various applications. The state of the art is the attention-based encoder-decoder framework that learns the mapping between input images and output sequences in a purely data-driven way. However, we observe that existing attention-based methods perform poorly on complicated and/or low-quality images. One major reason is that existing methods cannot get accurate alignments between feature areas and targets for such images. We call this phenomenon "attention drift". To tackle this problem, in this paper we propose the FAN (the abbreviation of Focusing Attention Network) method that employs a focusing attention mechanism to automatically draw back the drifted attention. FAN consists of two major components: an attention network (AN) that is responsible for recognizing character targets as in the existing methods, and a focusing network (FN) that is responsible for adjusting attention by evaluating whether AN pays attention properly on the target areas in the images. Furthermore, different from the existing methods, we adopt a ResNet-based network to enrich deep representations of scene text images. Extensive experiments on various benchmarks, including the IIIT5k, SVT and ICDAR datasets, show that the FAN method substantially outperforms the existing methods.
527 citations
TL;DR: It is suggested that, under appropriate conditions, spatial attention can be involuntarily drawn to abrupt-onset events despite the intention of subjects’ to ignore them.
Abstract: Five experiments were carried out to examine the extent to which brief abrupt-onset visual stimuli involuntarily capture spatial attention A fundumantal limitation on the conscious control of spatial attention is demonstrated Data obtained reveal conditions under which the control of spatial attention is completely involuntary: attention is captured by an irrelevant event despite subjects' intentions to ignore the event The paradigm used provided strong incentives to ignore the distracting abrupt onset, but these were insufficient to prevent capture Results suggest that voluntary control of attention is limited to focusing attention in advance on locations, objects, or properties of interest Under appropriate conditions, spatial attention can be involantarily drawn to abrupt-onset events despite the intention of subjects' to ignore them
449 citations
1 Oct 2017
TL;DR: Zhang et al. as mentioned in this paper proposed Focusing Attention Network (FAN) which employs a focusing attention mechanism to automatically draw back the drifted attention. But the FAN method is not suitable for complex and low-quality images and it cannot get accurate alignment between feature areas and targets for such images.
Abstract: Scene text recognition has been a hot research topic in computer vision due to its various applications. The state of the art is the attention-based encoder-decoder framework that learns the mapping between input images and output sequences in a purely data-driven way. However, we observe that existing attention-based methods perform poorly on complicated and/or low-quality images. One major reason is that existing methods cannot get accurate alignments between feature areas and targets for such images. We call this phenomenon “attention drift”. To tackle this problem, in this paper we propose the FAN (the abbreviation of Focusing Attention Network) method that employs a focusing attention mechanism to automatically draw back the drifted attention. FAN consists of two major components: an attention network (AN) that is responsible for recognizing character targets as in the existing methods, and a focusing network (FN) that is responsible for adjusting attention by evaluating whether AN pays attention properly on the target areas in the images. Furthermore, different from the existing methods, we adopt a ResNet-based network to enrich deep representations of scene text images. Extensive experiments on various benchmarks, including the IIIT5k, SVT and ICDAR datasets, show that the FAN method substantially outperforms the existing methods.
377 citations
TL;DR: D dorsal/caudal regions of the anterior cingulate cortex, thought to make a major contribution to cognitive control, boost attentional resources toward behaviorally relevant stimuli as a means for limiting the processing of distracting events are investigated.
Abstract: In everyday life, we often focus greater attention on behaviorally relevant stimuli to limit the processing of distracting events. For example, when distracting voices intrude upon a conversation at a noisy social gathering, we concentrate more attention on the speaker of interest to better comprehend his or her speech. In the present study, we investigated whether dorsal/caudal regions of the anterior cingulate cortex (dACC), thought to make a major contribution to cognitive control, boost attentional resources toward behaviorally relevant stimuli as a means for limiting the processing of distracting events. Sixteen healthy participants performed a cued global/local selective attention task while brain activity was recorded with event-related functional magnetic resonance imaging. Consistent with our hypotheses, greater dACC activity during distracting events predicted reduced behavioral measures of interference from those same events. dACC activity also differed for cues to attend to global versus local features of upcoming visual objects, further indicating a role in directing attention toward task-relevant stimuli. Our findings indicate a role for dACC in focusing attention on behaviorally relevant stimuli, especially when the achievement of our behavioral goals is threatened by distracting events.
315 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2021 | 2 |
| 2020 | 2 |
| 2019 | 8 |
| 2018 | 3 |
| 2017 | 7 |
| 2016 | 3 |