Multiple attributes of a single-object are often processed more easily than attributes of different objects-a phenomenon associated with object attention. Here we investigate the influence of two factors, judgment frames and judgment precision, on dual-object report deficits as an index of object attention. [Han, S., Dosher, B., & Lu, Z.-L. (2003). Object attention revisited: Identifying mechanisms and boundary conditions. Psychological Science, 14, 598-604] predicted that consistency of the frame for judgments about two separate objects could reduce or eliminate the expression of object attention limitations. The current studies examine the effects of judgment frames and of task precision in orientation identification and find that dual-object report deficits within one feature are indeed affected modestly by the congruency of the judgments and more substantially by the required precision of judgments. The observed dual-object deficits affected contrast thresholds for incongruent frame conditions and for high precision judgments and reduce psychometric asymptotes. These dual-object deficits reflect a combined effect of multiplicative noise and external noise exclusion in dual-object conditions, both related to the effects of attention on the tuning of perceptual templates. These results have implications for modification of object attention theory, for understanding limitations on concurrent tasks.
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http://dx.doi.org/10.1016/j.visres.2008.07.025 | DOI Listing |
Accid Anal Prev
January 2025
Department of Computer Engineering, Hongik University, Seoul, 04066, Republic of Korea. Electronic address:
Automated Vehicles (AVs) are on the cusp of commercialization, prompting global governments to organize the forthcoming mobility phase. However, the advancement of technology alone cannot guarantee the successful commercialization of AVs without insights into the accidents on the read roads where Human-driven Vehicles (HV) coexist. To address such an issue, The New Car Assessment Program (NCAP) is currently in progress, and scenario-based approaches have been spotlighted.
View Article and Find Full Text PDFJ Exp Psychol Learn Mem Cogn
December 2024
Technical University of Darmstadt, Institute of Psychology.
The goal of the present investigation was to perform a registered replication of Jones and Macken's (1995b) study, which showed that the segregation of a sequence of sounds to distinct locations reduced the disruptive effect on serial recall. Thereby, it postulated an intriguing connection between auditory stream segregation and the cognitive mechanisms underlying the irrelevant speech effect. Specifically, it was found that a sequence of changing utterances was less disruptive in stereophonic presentation, allowing each auditory object (letters) to be allocated to a unique location (right ear, left ear, center), compared to when the same sounds were played monophonically.
View Article and Find Full Text PDFTrends Hear
January 2025
Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Head and Neck Surgery, University of Cologne, Cologne, Germany.
Speech-on-speech masking is a common and challenging situation in everyday verbal communication. The ability to segregate competing auditory streams is a necessary requirement for focusing attention on the target speech. The Visual World Paradigm (VWP) provides insight into speech processing by capturing gaze fixations on visually presented icons that reflect the speech signal.
View Article and Find Full Text PDFBioinformatics
January 2025
School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China.
Motivation: Ensuring connectivity and preventing fractures in tubular object segmentation are critical for downstream analyses. Despite advancements in deep neural networks (DNNs) that have significantly improved tubular object segmentation, existing methods still face limitations. They often rely heavily on precise annotations, hindering their scalability to large-scale unlabeled image datasets.
View Article and Find Full Text PDFSci Rep
January 2025
School of Information Engineering, Shandong Huayu University of Technology, Dezhou, 253000, China.
In order to reduce the number of parameters in the Chinese herbal medicine recognition model while maintaining accuracy, this paper takes 20 classes of Chinese herbs as the research object and proposes a recognition network based on knowledge distillation and cross-attention - ShuffleCANet (ShuffleNet and Cross-Attention). Firstly, transfer learning was used for experiments on 20 classic networks, and DenseNet and RegNet were selected as dual teacher models. Then, considering the parameter count and recognition accuracy, ShuffleNet was determined as the student model, and a new cross-attention mechanism was proposed.
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