19 papers · ranked by Valyu relevance
L. Serriere, G. Argiris, J. Gomes, G.M. Giorjiani + 3 more
In our daily lives we encounter a myriad of things with which we might need to interact as we navigate our environment. Mental representations of these things must be computed and stored in our brains to be manipulated to support cognition. How are such representations organized in the brain? Several proposals have…
Alireza Javadi, Hamid Soltanian-Zadeh, Karim Rajaei
Coherent scenes facilitate object recognition, but the representational basis of this facilitation and its temporal evolution in the brain remain unclear. We tested this question using EEG and multivariate pattern analysis while 15 participants categorized objects from five semantic categories after a 500-ms preview of…
Wenhao Hou, Sheng He, Jiedong Zhang, Peter Kok + 1 more
Brain is a hierarchical information processing system, in which the feedback signals from high-level to low-level regions are critical. The feedback signals may convey complex high-order features (e.g. category, identity) and simple low-order features (e.g. orientation, spatial frequency) to sensory cortex to interact…
Niklas Müller, H. Steven Scholte, Iris I. A. Groen
In real-world vision, the human brain needs to process large amounts of information to effectively interact with its environment. It is well established that our visual system has specialized regions to process information efficiently, such as scene-, face-, and object-selective areas, which can be uncovered using…
Julien Dirani, Shankar Chawla, Leila Wehbe, Bradford Z. Mahon
The human brain represents objects in a way that is both invariant across instances and flexible enough to support different contexts and tasks. Yet it remains unknown how object representations are dynamically remapped as the same object shifts across contextual roles. Here we combined fMRI with naturalistic movie…
Alexis Kidder, Genevieve L. Quek, Tijl Grootswagers
How is object information organized in high-level visual cortex? A recent comprehensive model of object space in macaques defines object space via orthogonal axes of animacy and aspect ratio (i.e., stubby vs. spiky) ([2]). However, when using object stimuli that dissociated category, animacy, and aspect ratio in human…
Yihao Li, Saeed Salehi, Lyle Ungar, Konrad P. Kording
Object binding, the brain's ability to bind the many features that collectively represent an object into a coherent whole, is central to human cognition. It groups low-level perceptual features into high-level object representations, stores those objects efficiently and compositionally in memory, and supports human…
Ariel H. Kim, Genevieve L. Quek, Denise Moerel, Olivia Gorton + 1 more
Humans effortlessly relate what they see to what they know, drawing on existing knowledge of the perceptual, conceptual, and contextual attributes of objects while searching for and recognizing objects. Although prior studies have investigated the temporal dynamics of perceptual and conceptual object properties in the…
Andrey Gizdov, Andrea Procopio, Yichen Li, Daniel Harari + 1 more
Human physical reasoning relies on internal "body" representations — coarse, volumetric approximations that capture an object's extent and support intuitive predictions about motion and physics. While psychophysical evidence suggests humans use such coarse representations, their internal structure remains largely…
Alberto Ronzoni, Antony, Anina, M.P. Anjana + 7 more
The academic evolution of process mining is moving toward object centric process mining, marking a significant shift in how processes are modeled and analyzed. IBM has developed its own distinctive approach called Multilevel Process Mining. This paper provides a description of the two approaches and presents a…
Mohammad Wafa
The Hemispheric Disparity Theory conceptualizes one facet of consciousness, defined as the “conscious-mind” experience. Rather than a unified agent, conscious experience arises from the dynamic interplay between a left hemisphere specialized in order and abstraction through dynamic temporal modeling, and a right…
Yuanfang Zhao, Simen Hagen, Marius V. Peelen
Human visual cortex contains regions that selectively respond to both scenes and large objects, particularly buildings. The cortical overlap between buildings and scenes has been attributed to shared visual features (e.g., cardinal orientations, rectilinearity). Alternative accounts propose that buildings may also…
Netta Ollikka, Anni Bergström, Markku Kilpeläinen, Stéphane Deny
Mounting evidence suggests that recurrent processes in the visual system play a critical role during challenging recognition tasks. Backward masking techniques have traditionally been used as a non-invasive method for studying recurrent processes: A mask follows the target image, presumably disrupting ongoing…
Latif, Saba, Huma Latif, Muhammad Rameez Ur Rahman
Object Centric Event Data (OCED) has gained attention in recent years within the field of process mining. However, there are still many challenges, such as connecting the XES format to object-centric approaches to enable more insightful analysis. It is important for a process miner to understand the insights and…
Udith Haputhanthri, Declan Campbell, Rim Assouel, Jonathan D. Cohen + 1 more
Despite success on standard benchmarks, vision language models display persistent failures on tasks involving processing of multi-object scenes, including many tasks that are relatively easy for humans. Recent work has found that these failures may stem from a basic inability to accurately bind object features…
Abror Shavkatovich Buriboev, Akhram Nishanov, Shuxrat Isroilov, Inomjon Narzullaev + 7 more
Accurate classification of pollen grains in microscopic images remains challenging because of noise, structural variability, background complexity, weak texture, and intra-class similarity. To address these issues, this study proposes a hybrid framework that integrates contour-signal modeling, spectral-wavelet…
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Self-driving laboratories (SDLs) promise accelerated scientific discovery and product development by closing the loop between robotic execution and AI/ML-driven decision making. In practice, however, SDL orchestration remains fragmented; workflows are typically encoded as laboratory-specific scripts or bespoke…
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This comprehensive review examines the evolution of autonomous materials synthesis laboratories that integrate artificial intelligence with advanced robotics to accelerate discovery. Traditional materials development pipelines typically require 10-20 years, but self-driving laboratories (SDLs) and Materials…
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Iron, the most abundant element on Earth by mass (34.6%), primarily exists as iron minerals due to its inherent reactivity. The study of iron mineral phase transformations under changing environmental conditions remains an important research focus due to its geological, environmental, and industrial significance. Yet…