Humans can efficiently individuate a small number of objects. This subitizing ability is thought to be a consequence of limited attentional resources. However, how and what is selected during the individuation process remain outstanding questions. We investigated these in four experiments by examining if parts of objects are enumerated as efficiently as distinct objects in the presence and absence of distractor objects. We found that distractor presence reduced subitizing efficiency. Crucially, parts connected to multiple objects were enumerated less efficiently than independent objects or parts connected to a single object. These results argue against direct individuation of parts and show that objecthood plays a fundamental role in individuation. Objects are selected first and their components are selected in subsequent steps. This reveals that individuation operates sequentially over multiple levels.
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http://dx.doi.org/10.3758/s13423-020-01836-2 | DOI Listing |
Biosens Bioelectron
March 2025
Department of Biotechnology, National Formosa University, No. 64, Wunhua Rd, Huwei Township, Yunlin County, 63201, Taiwan. Electronic address:
The EZ DEVICE is an integrated fluorescence microflow cytometer designed for automated cell phenotyping and enumeration using artificial intelligence (AI). The platform consists of a laser diode, optical filter, objective lens, CMOS image sensor, and microfluidic chip, enabling automated sample pretreatment, labeling, and detection within a single compact unit. AI algorithms segment and identify objects in images captured by the CMOS sensor at 532 and 586 nm emission wavelengths.
View Article and Find Full Text PDFFront Med
December 2024
Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240, China.
Chromosome karyotyping is a critical way to diagnose various hematological malignancies and genetic diseases, of which chromosome detection in raw metaphase cell images is the most critical and challenging step. In this work, focusing on the joint optimization of chromosome localization and classification, we propose ChromTR to accurately detect and classify 24 classes of chromosomes in raw metaphase cell images. ChromTR incorporates semantic feature learning and class distribution learning into a unified DETR-based detection framework.
View Article and Find Full Text PDFPLoS One
November 2024
Fisheries and Oceans Canada, Freshwater Institute, Winnipeg, MB, Canada.
Very high-resolution (VHR) satellite imagery has proven to be useful for detection of large to medium cetaceans, such as odontocetes and offers some significant advantages over traditional detection methods. However, the significant time investment needed to manually read satellite imagery is currently a limiting factor to use this method across large open ocean regions. The objective of this study is to develop a semi-automated detection method using object-based image analysis to identify beluga whales (Delphinapterus leucas) in open water (summer) ocean conditions in the Arctic using panchromatic WorldView-3 satellite imagery and compare the detection time between human read and algorithm detected imagery.
View Article and Find Full Text PDFSci Rep
November 2024
School of Information Engineering, Huzhou University, Huzhou, 313000, China.
Neuron
December 2024
Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, UK. Electronic address:
To understand a visual scene, observers need to both recognize objects and encode relational structure. For example, a scene comprising three apples requires the observer to encode concepts of "apple" and "three." In the primate brain, these functions rely on dual (ventral and dorsal) processing streams.
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