27 papers · ranked by Valyu relevance
Tijl Grootswagers, Amanda K. Robinson, Sophia M. Shatek, Thomas A Carlson
The basic computations performed in the human early visual cortex are the foundation for visual perception. While we know a lot about these computations from work in non-human animals, a key missing piece is how the coding of visual features relates to our perceptual experience. To investigate visual feature coding…
Jan Kevin Schluesener, Malav Shah, Florian Sandhaeger, Markus Siegel
Neural activity is selective for the identity and semantic category of natural visual stimuli. In human neuroimaging, this selectivity can be investigated using multivariate pattern analysis. The resulting neural information is thought to reflect neural processes underlying object recognition. However, due to the…
Liqiang Huang
Visual features are often assumed to be the general building blocks for various visual tasks. However, it is well known that some stimulus categories (i.e., basic features) can be processed in parallel, but others (e.g., Ts in different orientations) need to be scanned serially, and this difference in featural strength…
Shijia Fan, Xiaosha Wang, Xiaoying Wang, Tao Wei + 1 more
Visual object recognition in humans and nonhuman primates is achieved by the ventral visual pathway (ventral occipital-temporal cortex, VOTC), which shows a well-documented object domain structure. An on-going question has been what type of information is processed in higher-order VOTC that underlies such observations…
Selim Onat, Alper Açık, Frank Schumann, Peter König + 1 more
During free-viewing of natural scenes, eye movements are guided by bottom-up factors inherent to the stimulus, as well as top-down factors inherent to the observer. The question of how these two different sources of information interact and contribute to fixation behavior has recently received a lot of attention. Here…
Javad Azimi, Ruofei Zhang, Yang Zhou, Vidhya Navalpakkam + 2 more
'Jianchang Mao' 'Xiaoli Z. Fern'] Display advertising has been a significant source of revenue for publishers and ad networks in online advertising ecosystem. One of the main goals in display advertising is to maximize user response rate for advertising campaigns, such as click through rates (CTR) or conversion rates.…
Seiichi Uchida
This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the…
Alessandro Betti, Giuseppe Boccignone, Lapo Faggi, Marco Gori + 1 more
Symmetries, invariances and conservation equations have always been an invaluable guide in Science to model natural phenomena through simple yet effective relations. For instance, in computer vision, translation equivariance is typically a built-in property of neural architectures that are used to solve visual tasks…
Rubi Hammer
People have to sort numerous objects into a large number of meaningful categories while operating in varying contexts. This requires identifying the visual features that best predict the ‘essence’ of objects (e.g., edibility), rather than categorizing objects based on the most salient features in a given context. To…
Margaret Henderson, Michael J. Tarr, Leila Wehbe
Representations of visual and semantic information can overlap in human visual cortex, with the same neural populations exhibiting sensitivity to low-level features (orientation, spatial frequency, retinotopic position), and high-level semantic categories (faces, scenes). It has been hypothesized that this relationship…
Arjen Alink, Ian Charest
Individuals with an autism spectrum disorder (ASD) diagnosis are often described as having an ‘eye for detail’1. This observation, and the finding that individuals with ASD tend to ‘see the trees before the forest’ when performing the Navon task2, has led to the proposal that ASD is characterized by a bias towards…
Andrés Hernández-Serna, Luz Fernanda Jiménez-Segura, Mark Costello
A new automatic identification system using photographic images has been designed to recognize fish, plant, and butterfly species from Europe and South America. The automatic classification system integrates multiple image processing tools to extract the geometry, morphology, and texture of the images. Artificial…
Henan Zhao, Jian Chen
—We present study results from two experiments to empirically validate that separable bivariate pairs for univariate representations of large-magnitude-range vectors are more efficient than integral pairs. The first experiment with 20 participants compared: one integral pair, three separable pairs, and one redundant…
Kevin Mildau, Christoph Büschl, Jürgen Zanghellini, Justin J.J. van der Hooft
Computational metabolomics workflows have revolutionized the untargeted metabolomics field. However, the organization and prioritization of metabolite features remains a laborious process. Organizing metabolomics data is often done through mass fragmentation-based spectral similarity grouping, resulting in feature sets…
Chen Zhao, Luming Hu, Liuqing Wei, Chundi Wang + 3 more
'Xuemin Zhang'] In real-world scenarios, objects’ surface features sometimes change as they move, impairing the continuity of objects. However, it is still unknown how our visual system adapts to this dynamic change. Hence, the present study investigated the role of feature changes in attentive tracking through a…
Jayani P. G. Lakshika, Thiyanga S. Talagala
Plant species identification is time-consuming, costly, and requires lots of effort, and expert knowledge. The studies on medicinal plant identification are often performed based on medicinal plant leaf images. The is because plant leaves contain a large number of diverse sets of features such as shape, veins, edge…
Sergio Pablo-García, Raúl Pérez-Soto, Albert Sabadell-Rendón, Diego Garay-Ruiz + 2 more
In the study of chemical reactions, visualizing reaction networks is pivotal for identifying crucial compounds and reactions. Traditional methods, such as network schematics and reaction path linear plots, often struggle to effectively represent complex reaction networks due to their size and intricate connectivity.…
David Berga, Xosé R. Fdez-Vidal, Xavier Otazu, Víctor Leborán + 1 more
'Xosé M. Pardo'] In this study we provide the analysis of eye movement behavior elicited by low-level feature distinctiveness with a dataset of synthetically-generated image patterns. Design of visual stimuli was inspired by the ones used in previous psychophysical experiments, namely in free-viewing and visual…
Jacopo Iacovacci, Lucas Lacasa
The family of image visibility graphs (IVGs) have been recently introduced as simple algorithms by which scalar fields can be mapped into graphs. Here we explore the usefulness of such operator in the scenario of image processing and image classification. We demonstrate that the link architecture of the image…
Daniela Valério, Akbar Hussain, Jorge Almeida
Feature generation tasks and feature databases are important for understanding how knowledge is organized in semantic memory, as they reflect not only the kinds of information that individuals have about objects but also how objects are conceptually parse. Traditionally, semantic norms focus on a variety of object…
Authors not listed
In experimental chemistry, actions are adjusted based on what we see—such as dosing until dissolution, heating until melting, or stirring until mixing is complete. However, current self-driving labs (SDLs) do not monitor these visual cues. HeinSight 4.0 fills this gap by integrating computer vision into SDLs to enable…
Yaocong Duan, Jiayu Zhan, Joachim Groß, Robin A. A. Ince + 1 more
'Philippe G. Schyns'] Visual categorization is the pervasive cognitive function with which humans make sense of their external world. Current theories and models assume that the visual hierarchy reduces its high-dimensional input, by flexibly selecting the stimulus features that support categorization behavior. To…
Artem Lenskiy
PREPRINTAbstract—Computer vision has become a major source of information for autonomous navigation of robots of various types, self-driving cars, military robots and mars/lunar rovers are some examples. Nevertheless, the majority of methods focus on analysing images captured in visible spectrum. In this manuscript we…
Fares Jalled, Voronkov Ilia
—An Unmanned Ariel vehicle (UAV) has greater importance in the army for border security. The main objective of this article is to develop an OpenCV-Python code using Haar Cascade algorithm for object and face detection. Currently, UAVs are used for detecting and attacking the infiltrated ground targets. The main…
Murat Cihan Sorkun, Dajt Mullaj, J. M. Vianney A. Koelman, Süleyman Er
Visualizing chemical spaces streamlines the analysis of molecular datasets by reducing the information to human perception level, hence it forms an integral piece of molecular engineering, including chemical library design, high-throughput screening, diversity analysis, and outlier detection. We present here ChemPlot…
Authors not listed
Traditional and non-classical machine learning models for solid-state structure prediction have predominantly relied on compositional features (derived from properties of constituent elements) to predict the existence of structure and its properties. However, the lack of structural information can be a source of…
Heeseung Lee, Daeho Kim, Heyin Lee, Namyoung Gwak + 6 more
- 1. Computational Science Research Center, Korea Institute of Science and Technology, Seoul 02792, Republic of Korea - 2. Department of Materials Science and Engineering, Korea University, 145 Anam-ro, Seoul 02841, Republic of Korea - 3. Department of Chemical and Biological Engineering, Korea University, Seoul 02841…