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Search · four archives
24 papers · ranked by Valyu relevance
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…
Lior Shamir, John D. Delaney, Nikita Orlov, D. Mark Eckley + 2 more
'Ilya G. Goldberg' 'Fran Lewitter'] The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image…
Andrew Gleibman
The first contribution of this paper is architecture of a multipurpose system, which delegates a range of object detection tasks to a classifier, applied in special grid positions of the tested image. The second contribution is Gray Level-Radius Co-occurrence Matrix, which describes local image texture and topology…
Yonghong Chen
Every pattern is a 3-dimensional graph, its surface can be split up into some regions, every region is composed of the pixels with the approximately same colour value and the approximately same depth value that is distance to eyes, and there may also be some contours, e.g., literal contours, on a surface of every…
Yufeng Zheng, Erik Blasch, Adel S. Elmaghraby
State-of-the-art image analysis and pattern recognition techniques have been successfully applied to a wide variety of industrial fields such as medical imaging, remote sensing, and biometrics, as well as methods for machine learning, computer vision, and visualization. However, the current methods of image analysis…
Evgeny Gladilin, Roland Eils
Numerous findings indicate that spatial phase bears an important cognitive information. Distortion of phase affects topology of edge structures and makes images unrecognizable. In turn, appropriately phase-structured patterns give rise to various illusions of virtual image content and apparent motion. Despite a large…
Rama Chellappa, Jun-Cheng Chen, Rajeev Ranjan, Swami Sankaranarayanan + 3 more
'Swami Sankaranarayanan' 'Amit Kumar' 'Vishal M. Patel' 'Carlos D. Castillo'] Abstract—Over many decades, researchers working in object recognition have longed for an end-to-end automated system that will simply accept 2D or 3D image or videos as inputs and output the labels of objects in the input data. Computer…
Abdulwahab Alazeb, Bisma Riaz Chughtai, Naif Al Mudawi, Yahya AlQahtani + 4 more
'Yahya AlQahtani' 'Mohammed Alonazi' 'Hanan Aljuaid' 'Ahmad Jalal' 'Hui Liu'] Introduction During the last few years, a heightened interest has been shown in classifying scene images depicting diverse robotic environments. The surge in interest can be attributed to significant improvements in visual sensor technology…
Alan Yuille, Daniel Kersten
This document presents an introduction to computer vision, and its relationship to Cognitive Science, from the perspective of Bayes Decision Theory (Berger 1985). Computer vision is a vast and complex field, so this overview has a narrow scope and provides a theoretical lens which captures many key concepts. BDT is…
Yaser Daanial Khan, Nabeel Sabir Khan, Shoaib Farooq, Adnan Abid + 3 more
'Sher Afzal Khan' 'Farooq Ahmad' 'M. Khalid Mahmood'] Recognition of human actions is an emerging need. Various researchers have endeavored to provide a solution to this problem. Some of the current state-of-the-art solutions are either inaccurate or computationally intensive while others require human intervention. In…
Wei Wang
The problem of optical character recognition, OCR, has been widely discussed in the literature. Having a hand-written text, the program aims at recognizing the text. Even though there are several approaches to this issue, it is still an open problem. In this paper we would like to propose an approach that uses…
Peng Peng, Ivens Portugal, Paulo Alencar, Donald Cowan + 1 more
analysis A face recognition software framework based on principal component analysis Authors: ['Peng Peng' 'Ivens Portugal' 'Paulo Alencar' 'Donald Cowan' 'Robertas Damaševičius'] Face recognition, as one of the major biometrics identification methods, has been applied in different fields involving economics, military…
Mozhgan Shahmohammadi, Ehsan Vahab, Hamid Karimi-Rouzbahani
In order to develop object recognition algorithms, which can approach human-level recognition performance, researchers have been studying how the human brain performs recognition in the past five decades. This has already in-spired AI-based object recognition algorithms, such as convolutional neural networks, which are…
Divyarajsinh N. Parmar, Brijesh B. Mehta
- Face recognition presents a challenging problem in the field of image analysis and computer vision. The security of information is becoming very significant and difficult. Security cameras are presently common in airports, Offices, University, ATM, Bank and in any locations with a security system. Face recognition is…
Emmanuel Daucé, Pierre Albiges, Laurent Perrinet
Visual search involves a dual task of localizing and categorizing an object in the visual field of view. We develop a visuo-motor model that implements visual search as a focal accuracy-seeking policy, and we assume that the target position and category are random variables which are independently drawn from a common…
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…
Matteo Dunnhofer, Jean de dieu Uwisengeyimana, Kohitij Kar
How does motion contribute to robust object perception when appearance cues are unreliable? In natural scenes, camouflage, clutter, and occlusion can obscure object boundaries in static images, yet humans often resolve these ambiguities once objects move. Here we ask whether modern artificial vision systems capture…
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…
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…
Moshe Gur
Object recognition models have at their core similar essential characteristics: feature extraction and hierarchical convergence leading to a code that is unique to each object and immune to variations in the object appearance. To compare computational, biologically-feasible models to human performance, subjects viewed…
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…
Caominh Le, Samantha Pedersen, Nathaniel Chen, Jonathan Chan + 28 more
Human vision has a remarkable ability to recognize complex 3D objects such as faces that appear at any size and 3D orientations at any 3D location. If we initially memorize a face only with a normalized size upfront at the object center, the direct comparison between the one-sized memory and an incoming new image would…
Authors not listed
Predicting protein-ligand binding affinity from three-dimensional (3D) structural data is a central task in structure-based drug discovery, yet it remains challenging due to limited data availability, structural complexity, and the sparse nature of 3D molecular representations. In this study, we investigate the…
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…