29 papers · ranked by Valyu relevance
Susan G. Wardle, Chris I. Baker
Object recognition is the ability to identify an object or category based on the combination of visual features observed. It is a remarkable feat of the human brain, given that the patterns of light received by the eye associated with the properties of a given object vary widely with simple changes in viewing angle…
Svetlana Volotsky, Ohad Ben-Shahar, Opher Donchin, Ronen Segev
Recognition of individual objects and their categorization is a complex computational task. Nevertheless, visual systems are able to perform this task in a rapid and accurate manner. Humans and other animals can efficiently recognize objects despite countless variations in their projection on the retina due to…
Imran Khan Mirani, Tianhua Chen, Malak Abid Ali Khan, Syed Muhammad Aamir + 1 more
'Syed Muhammad Aamir' 'Waseef Menhaj'] Imran Khan Mirani a , Chen Tianhuab , Malak Abid Ali Khanc , Syed Muhammad Aamirc , Waseef Menhajd a School of Information and Computer Engineering, Beijing University of Technology, Beijing, 100124, China b School of Artificial Intelligence, Beijing Technology & Business…
D. Anitta, A. Annis Fathima
--- Computer vision helps machines or computer to see like humans. Computer Takes information from the images and then understands of useful information from images. Gesture recognition and movement recognition are the current area of research in computer vision. For both gesture and movement recognition finding pose…
Irina M. Harris
Is object orientation an inherent aspect of the shape of the object or is it represented separately and bound to the object shape in a similar way to other features, such as colour? This review brings together findings from neuropsychological studies of patients with agnosia for object orientation and experimental…
Hui Wei, Tang Fuyu
—Artificial objects usually have very stable shape features, which are stable, persistent properties in geometry. They can provide evidence for object recognition. Shape features are more stable and more distinguishing than appearance features, color features, grayscale features, or gradient features. The difficulty…
Randall C. O’Reilly, Dean Wyatte, Seth Herd, Brian Mingus + 1 more
'David J. Jilk'] How does the brain learn to recognize objects visually, and perform this difficult feat robustly in the face of many sources of ambiguity and variability? We present a computational model based on the biology of the relevant visual pathways that learns to reliably recognize 100 different object…
Kosuke Nishida, Isamu Motoyoshi
Visual object and scene recognition have been extensively studied, but separately. We here propose that the two processes could be intrinsically linked in the neural system. We developed a Joint Residual Variational Autoencoder (JRVAE) with two networks: VAE1 for coarse scene recognition and VAE2 for object recognition…
László Czúni, Metwally Rashad
In the last few years, there has been a steadily growing interest in autonomous vehicles and robotic systems. While many of these agents are expected to have limited resources, these systems should be able to dynamically interact with other objects in their environment. We present an approach where lightweight sensory…
Oliver Lomp, Christian Faubel, Gregor Schöner
Handling objects or interacting with a human user about objects on a shared tabletop requires that objects be identified after learning from a small number of views and that object pose be estimated. We present a neurally inspired architecture that learns object instances by storing features extracted from a single…
Dan Malowany, Hugo Guterman
Computer vision is currently one of the most exciting and rapidly evolving fields of science, which affects numerous industries. Research and development breakthroughs, mainly in the field of convolutional neural networks, opened the way to unprecedented sensitivity and precision in object detection and recognition…
Hamidreza Kasaei
| presidente / president | Professor Doutor Helmuth Robert Malonek | | --- | --- | | | Professor Catedrático da Universidade de Aveiro | | vogais / examiners committee | Doutor Luís Filipe Barbosa de Almeida Alexandre | | | Professor Catedrático da Universidade da Beira Interior | | | Doutor Alexandre José Malheiro…
Susan G. Wardle, Beth Rispoli, Vinai Roopchansingh, Chris I. Baker
Humans are skilled at recognizing everyday objects from pictures, even if we have never encountered the depicted object in real life. But if we have encountered an object, how does that real-world experience affect the representation of its photographic image in the human brain? We developed a paradigm that involved…
Aylin Kallmayer, Melissa L.-H. Võ, Dejan Draschkow
Viewpoint effects on object recognition interact with object-scene consistency effects. While recognition of objects seen from “accidental” viewpoints (e.g., a cup from below) is typically impeded compared to processing of objects seen from canonical viewpoints (e.g., the string-side of a guitar), this effect is…
David A. Nicholson, Astrid A. Prinz
To find an object we are looking for, we must recognize it. Prevailing models of visual search neglect recognition, focusing instead on selective attention mechanisms. These models account for performance limitations that participants exhibit when searching highly simplified stimuli often used in laboratory tasks.…
Lanqing Huang, Cheng Yao, Lingyan Zhang, Shijian Luo + 2 more
'Weiqiang Ying'] Advances in computer image recognition have significantly impacted many industries, including healthcare, security and autonomous systems. This paper aims to explore the potential of improving image algorithms to enhance computer image recognition. Specifically, we will focus on regression methods as a…
Nasim Hajari, Gabriel Lugo Bustillo, Harsh Sharma, Irene Cheng
The task of recognising an object and estimating its 6d pose in a scene has received considerable attention in recent years. The accessibility and low-cost of consumer RGB-D cameras, make object recognition and pose estimation feasible even for small industrial businesses. An example is the industrial assembly line…
Dorian Gálvez‐López, Marta Salas, Juan D. Tardós, J. M. M. Montiel
We present a real-time object-based SLAM system that leverages the largest object database to date. Our approach comprises two main components: 1) a monocular SLAM algorithm that exploits object rigidity constraints to improve the map and find its real scale, and 2) a novel object recognition algorithm based on bags of…
Cheryl A. Olman, Tori Espensen-Sturges, Isaac Muscanto, Julia M. Longenecker + 4 more
Visual object recognition is a complex skill that relies on the interaction of many spatially distinct and specialized visual areas in the human brain. One tool that can help us better understand these specializations and interactions is a set of visual stimuli that do not differ along low-level dimensions (e.g.…
Isaac Ronald Ward, Hamid Laga, Mohammed Bennamoun
Object detection from RGB images is a long-standing problem in image processing and computer vision. It has applications in various domains including robotics, surveillance, human-computer interaction, and medical diagnosis. With the availability of low cost 3D scanners, a large number of RGB-D object detection…
Inbar Huberman, Raanan Fattal
In this paper we describe a new method for detecting and counting a repeating object in an image. While the method relies on a fairly sophisticated deformable part model, unlike existing techniques it estimates the model parameters in an unsupervised fashion thus alleviating the need for a user-annotated training data…
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…
Kohulan Rajan, Henning Otto Brinkhaus, M. Isabel Agea, Achim Zielesny + 1 more
The number of publications describing chemical structures has increased steadily over the last decades. However, the majority of published chemical information is currently not available in machine-readable form in public databases. It remains a challenge to automate the process of information extraction in a way that…
Kohulan Rajan, Henning Otto Brinkhaus, Achim Zielesny, Christoph Steinbeck
Accurate recognition of hand-drawn chemical structures is crucial for digitising hand-written chemical information found in traditional laboratory notebooks or for facilitating stylus-based structure entry on tablets or smartphones. However, the inherent variability in hand-drawn structures poses challenges for…
Alexander E. Siemenn, Eunice Aissi, Fang Sheng, Armi Tiihonen + 3 more
In materials research, the task of characterizing hundreds of different materials traditionally requires equally many human hours spent measuring samples one by one. We demonstrate that with the integration of computer vision into this material research workflow, many of these tasks can be automated, significantly…
Henning Otto Brinkhaus, Achim Zielesny, Christoph Steinbeck, Kohulan Rajan
The translation of images of chemical structures into machine-readable representations of the depicted molecules is known as optical chemical structure recognition (OCSR). There has been a lot of progress over the last three decades in this field, but the development of systems for the recognition of complex hand-drawn…
Lutz Weber, Aleksei Krasnov, Shadrack Barnabas, Timo Böhme + 1 more
The extraction of chemical information from images, also known as Optical Chemical Structure Recognition (OCSR) has recently gained new attention. This new interest is ignited by various machine learning methods introduced over the last years and the new possibilities to train image models for specific tasks such as…
Justus T. Metternich, Sujit K. Patjoshi, Tanuja Kistwal, Sebastian Kruss
Optical sensors/probes are powerful tools to identify and image (biological) molecules. Because of their optoelectronic properties, nanomaterials are often used as building blocks. Such nanosensors are assembled from an optically sensitive nanomaterial, a (biological) recognition unit, and linker chemistry that…
Authors not listed
Stretches of double-stranded DNA sharing the same sequence can recognise each other in cells. This phenomenon, known as homologous recognition, is essential for DNA recombination and repair. Yet, its mechanism remains debated, with purely physical duplex duplex interactions being proposed as a contributing factor.…