27 papers · ranked by Valyu relevance
Martin N Hebart, Brett B Bankson, Assaf Harel, Chris I Baker + 2 more
'Radoslaw M Cichy' 'Jody C Culham'] Despite the importance of an observer’s goals in determining how a visual object is categorized, surprisingly little is known about how humans process the task context in which objects occur and how it may interact with the processing of objects. Using magnetoencephalography (MEG)…
Alexandra Krugliak, Dejan Draschkow, Melissa L.-H. Võ, Alex Clarke
We typically encounter objects in a context, for example, a sofa in a living room or a car in the street, and this context influences how we recognize objects. Objects that are congruent with a scene context are recognised faster and more accurately than objects that are incongruent. Furthermore, objects that are…
Alexandra Krugliak, Dejan Draschkow, Melissa L.-H. Võ, Alex Clarke
Objects that are congruent with a scene are recognised more efficiently than objects that are incongruent. Further, semantic integration of incongruent objects elicits a stronger N300/N400 EEG component. Yet, the time course and mechanisms of how contextual information supports access to semantic object information is…
Talia Brandman, Marius V. Peelen
Real-world scenes consist of objects, defined by local information, and scene background, defined by global information. While objects and scenes are processed in separate pathways in visual cortex, their processing interacts. Specifically, previous studies have shown that scene context makes blurry objects look…
Talia Brandman, Marius V. Peelen
We internally represent the structure of our surroundings even when there is little layout information available in the visual image, such as when walking through fog or darkness. One way in which we disambiguate such scenes is through object cues; for example, seeing a boat supports the inference that the foggy scene…
M.N. Hebart, B.B. Bankson, A. Harel, C.I. Baker + 1 more
Object recognition is commonly described as a feedforward process, yet the tasks we carry out often affect what information in visual stimuli is diagnostic and may influence their processing. Surprisingly little is known about how task context is processed and when and how it interacts with the emerging representation…
Benjamin Peters, Nikolaus Kriegeskorte
Human visual perception carves a scene at its physical joints, decomposing the world into objects, which are selectively attended, tracked, and predicted as we engage our surroundings. Object representations emancipate perception from the sensory input, enabling us to keep in mind that which is out of sight and to use…
Karim Rajaei, Yalda Mohsenzadeh, Reza Ebrahimpour, Seyed-Mahdi Khaligh-Razavi
Core object recognition, the ability to rapidly recognize objects despite variations in their appearance, is largely solved through the feedforward processing of visual information. Deep neural networks are shown to achieve human-level performance in these tasks, and explain the primate brain representation. On the…
Karim Rajaei, Yalda Mohsenzadeh, Reza Ebrahimpour, Seyed-Mahdi Khaligh-Razavi + 1 more
'Seyed-Mahdi Khaligh-Razavi' 'Leyla Isik'] Core object recognition, the ability to rapidly recognize objects despite variations in their appearance, is largely solved through the feedforward processing of visual information. Deep neural networks are shown to achieve human-level performance in these tasks, and explain…
Arif ul Maula Khan, Ralf Mikut, Markus Reischl, Jie Tian
The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels…
Danaja Rutar, Alva Markelius, Konstantinos Voudouris, José Hernández-Orallo + 1 more
'José Hernández-Orallo' 'Lucy Cheke'] One of the core components of our world models is 'intuitive physics'—an understanding of objects, space, and causality. This capability enables us to predict events, plan action and navigate environments, all of which rely on a composite sense of objecthood. Despite its…
Miles Wischnewski, Marius V. Peelen
Objects can be recognized based on their intrinsic features, including shape, color, and texture. In daily life, however, such features are often not clearly visible, for example when objects appear in the periphery, in clutter, or at a distance. Interestingly, object recognition can still be highly accurate under…
Martin N. Hebart, Adam H. Dickter, Alexis Kidder, Wan Y. Kwok + 4 more
'Anna Corriveau' 'Caitlin Van Wicklin' 'Chris I. Baker' 'Fabian A. Soto'] In recent years, the use of a large number of object concepts and naturalistic object images has been growing strongly in cognitive neuroscience research. Classical databases of object concepts are based mostly on a manually curated set of…
Olivia S. Cheung, Isabel Gauthier
Objects contain rich visual and conceptual information, but do these two types of information interact? Here, we examine whether visual and conceptual information interact when observers see novel objects for the first time. We then address how this interaction influences the acquisition of perceptual expertise. We…
Elissa M. Aminoff, Tess Durham
Objects are fundamental to scene understanding. Scenes are defined by embedded objects and how we interact with them. Paradoxically, scene processing in the brain is typically discussed in contrast to object processing. Using the BOLD5000 dataset (11), we examined whether objects within a scene predicted the neural…
Frauke Hildebrandt, Jan Lonnemann, Ramiro Glauer
It counts as empirically proven that infants can individuate objects. Object individuation is assumed to be fundamental in the development of infants’ ontology within the object-first account. It crucially relies on an object-file (OF) system, representing both spatiotemporal (“where”) and categorical (“what”)…
Helmi Ben Hmida, Christophe Cruz, Frank Boochs, Christophe Nicolle
—This paper presents a knowledge-based detection of objects approach using the OWL ontology language, the Semantic Web Rule Language, and 3D processing built-ins aiming at combining geometrical analysis of 3D point clouds and specialist's knowledge. Here, we share our experience regarding the creation of 3D semantic…
Fausto Giunchiglia, Mayukh Bagchi
We base our work on the teleosemantic modelling of concepts as abilities implementing the distinct functions of recognition and classification. Accordingly, we model two types of concepts - substance concepts suited for object recognition exploiting visual properties, and classification concepts suited for…
Alessandro Berti, István Koren, Jan Niklas Adams, Gyunam Park + 9 more
'Benedikt Knopp' 'Nina Graves' 'Majid Rafiei' 'Lukas Liß' 'Leah Tacke Genannt Unterberg' 'Yisong Zhang' 'Christopher T. Schwanen' 'Marco Pegoraro' 'Wil M. P. van der Aalst'] Object-Centric Event Logs (OCELs) form the basis for Object-Centric Process Mining (OCPM). OCEL 1.0 was first released in 2020 and triggered the…
Eelke Spaak, Marius V. Peelen, Floris P. de Lange
Visual scene context is well-known to facilitate the recognition of scene-congruent objects. Interestingly, however, according to the influential theory of predictive coding, scene congruency should lead to reduced (rather than enhanced) processing of congruent objects, compared to incongruent ones, since congruent…
Authors not listed
Deriving versatile and robust mechanistic models from experimental data is a key challenge in engineering and natural sciences. This is especially true in chemical reaction engineering, where reactor manufacturers and operators increasingly pursue the development and maintenance of digital twins that rely on frequent…
Rama El-khawaldeh, Mason Guy, Finn Bork, Nina Taherimakhsousi + 6 more
This work presents a generalizable computer vision (CV) and machine learning model that is used for automated real-time monitoring and control of a diverse array of workup processes. Our system simultaneously monitors multiple physical parameters (e.g., liquid level, homogeneity, turbidity, solid, residue, and color)…
Alexandre Goossens, Johannes De Smedt, Jan Vanthienen, Wil M. P. van der Aalst
'Wil M. P. van der Aalst'] Abstract. When multiple objects are involved in a process, there is an opportunity for processes to be discovered from different angles with new information that previously might not have been analyzed from a single object point of view. This does require that all the information of…
Authors not listed
Vat photopolymerization (VP) is widely used for additive manufacturing due to its speed, precision, and material versatility. However, traditional support structures limit printable geometries, require manual post-processing, and produce non-recyclable waste. We introduce a wavelength-selective resin for VP that…
Authors not listed
This research presents a novel approach to obstacle detection during navigation using a combination of Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. The primary objective is to generate accurate image captions that describe the content of images, which is crucial for applications such…
Aaron Liu, Myeongyeon Lee, Rahul Venkatesh, Jessica Bonsu + 4 more
Polymer-based semiconductors and organic electronics encapsulate a significant research thrust for informatics-driven materials development. However, device measurements are described by a complex array of design and parameter choices, many of which are sparsely reported. For example, the mobility of a polymer-based…
Riley Hickman, Priyansh Parakh, Austin Cheng, Qianxiang Ai + 3 more
Experiment planning algorithms are a required component of autonomous platforms for scientific discovery. Selecting a suitable optimization algorithm for a novel application is an important yet difficult choice a researcher has to make based on past empirical performance on similar tasks. To facilitate the evaluation…