The saliency map is a computational model and has been constructed for simulating human saliency processing, e.g. pop-out target detection (e.g. Itti & Koch, 2000). In this study the spatial structure on the saliency map was investigated. It is proposed that the saliency map is structured into processing units whose size is increasing with retinal eccentricity. In two experiments the distance between a target in the stimulus and an irrelevant structure in the mask was varied systematically. Our findings had two main points. Firstly, in texture segmentation tasks the saliency signals from two texture irregularities interfere, when these irregularities appear within a critical spatial distance. Second, the critical distances increase with target eccentricity. The eccentricity-dependent critical distances can be interpreted as crowding effects. It is assumed that additionally to the target eccentricity, also the strength of a saliency signal can determine the spatial area of its impairing influence.
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http://dx.doi.org/10.1016/j.visres.2010.09.010 | DOI Listing |
World J Surg
December 2024
Monash University Endocrine Surgery Unit, Department of General Surgery, Alfred Hospital, Melbourne, Victoria, Australia.
Background: Despite widespread use of standardized classification systems, risk stratification of thyroid nodules is nuanced and often requires diagnostic surgery. Genomic sequencing is available for this dilemma however, costs and access restricts global applicability. Artificial intelligence (AI) has the potential to overcome this issue nevertheless, the need for black-box interpretability is pertinent.
View Article and Find Full Text PDFJ Evid Based Med
December 2024
Centre for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Objectives: Pregnant women had a large demand for diagnosis and treatment, but the clinical research was not sufficient, and there were many barriers for pregnant women to participate in clinical research. This study aimed to systematically identify these barriers and facilitators, map them with Theoretical Domains Framework (TDF) and Behavior Change Techniques (BCTs) to inform the development of interventions promoting pregnant women's involvement in clinical research.
Methods: This was a mixed-methods systematic review.
Neural Netw
December 2024
State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an, 710071, Shanxi, China.
Hyperspectral anomaly detection (HAD) aims to localize pixel points whose spectral features differ from the background. HAD is essential in scenarios of unknown or camouflaged target features, such as water quality monitoring, crop growth monitoring and camouflaged target detection, where prior information of targets is difficult to obtain. Existing HAD methods aim to objectively detect and distinguish background and anomalous spectra, which can be achieved almost effortlessly by human perception.
View Article and Find Full Text PDFSensors (Basel)
November 2024
School of Comuputer Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, China.
Focusing on the issue of the low recognition rates achieved by traditional deep-information-based action recognition algorithms, an action recognition approach was developed based on skeleton spatial-temporal and dynamic features combined with a two-stream convolutional neural network (TS-CNN). Firstly, the skeleton's three-dimensional coordinate system was transformed to obtain coordinate information related to relative joint positions. Subsequently, this relevant joint information was encoded as a color texture map to construct the spatial-temporal feature descriptor of the skeleton.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
Department of Computer Science, Chungbuk National University, Cheongju 28644, Republic of Korea.
Background: Tibiofibula fractures occur across all age groups, and postoperative complications are frequent. An accurate and rapid classification methodology for these fractures could significantly assist physicians. Clinically, tibiofibula fractures occur at various locations, and the fracture types are not evenly distributed.
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