Search · four archives
Search · four archives
26 papers · ranked by Valyu relevance
Shiyao Chen, Dale Chen-Song
For humans, object detection, recognition, and tracking are innate. These provide the ability for human to perceive their environment and objects within their environment. This ability however doesn't translate well in computers. In Computer Vision and Multimedia, it is becoming increasingly more important to detect…
Guangyi Chen, Adam Krzyzak, Eui Chul Lee
In this paper, we propose a novel method for 2D pattern recognition by extracting features with the log-polar transform, the dual-tree complex wavelet transform (DTCWT), and the 2D fast Fourier transform (FFT2). Our new method is invariant to translation, rotation, and scaling of the input 2D pattern images in a…
Dawei Zhang, Tingting Yang
Eye tracking is currently a research hotspot in the territory of service robotics. There is an urgent need for machine vision technique in the territory of video surveillance, and biological visual object following is one of the important basic research problems. By tracking the object of interest and recording the…
Gabriel G. De la Torre
Ahuna Mons is a 4 km particular geologic feature on the surface of Ceres, of possibly cryovolcanic origin. The special characteristics of Ahuna Mons are also interesting in regard of its surrounding area, especially for the big crater beside it. This crater possesses similarities with Ahuna Mons including diameter…
Gaurav Malhotra, Marin Dujmović, Jeffrey S Bowers
A central problem in vision sciences is to understand how humans recognise objects under novel viewing conditions. Recently, statistical inference models such as Convolutional Neural Networks (CNNs) seem to have reproduced this ability by incorporating some architectural constraints of biological vision systems into…
Shilpa Rani, Deepika Ghai, Sandeep Kumar, MVV Prasad Kantipudi + 2 more
In computer vision and medical image processing, object recognition is the primary concern today. Humans require only a few milliseconds for object recognition and visual stimulation. This led to the development of a computer-specific pattern recognition method in this study for identifying objects in medical images…
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…
Wenjing Shi
I would first like to thank my thesis advisor Prof. Marios S. Pattichis. The results described in this thesis were accomplished with his participation and guidance. I would also like to thank my committee members, Prof. Sylvia Celedon-Pattichis, Prof. Ramiro Jordan, and Dr. Sergio Murillo, for their dedication and…
Boros, Emanuela
Topological localization is a fundamental problem in mobile robotics. Most mobile robots must be able to self-locate in their environment in order to accomplish their tasks. Robot visual localization and place recognition are not easy tasks, and this is mainly due to the perceptive ambiguity of acquired data and the…
Sukhdeep Singh, Sudhir Rohilla, Anuj Sharma
handwriting recognition Authors: ['Sukhdeep Singh' 'Sudhir Rohilla' 'Anuj Sharma'] Deep learning expresses a category of machine learning algorithms that have the capability to combine raw inputs into intermediate features layers. These deep learning algorithms have demonstrated great results in different fields. Deep…
Héctor Guillen-Bonilla, José Trinidad Guillen-Bonilla, Maricela Jiménez-Rodríguez, Alex Guillen-Bonilla + 4 more
In this paper, an RGB image with $S$ is separated by its channels, obtaining an image in each color channel $S_{R}$, $S_{G}$ and $S_{B}$. The Vectorial Image Representation on the Texture Space (VIR-TS) transform is calculated for each channel; ergo, each image is represented with a given vector, $S_{R}\rightarrow…
Musarrat Saberin Nipun, Rejwan Bin Sulaiman, Amer Kareem
Face detection and identification is the most difficult and often used task in Artificial Intelligence systems. The goal of this study is to present and compare the results of several face detection and recognition algorithms used in the system. This system begins with a training image of a human, then continues on to…
Sana Ullah, Jie Ou, Yuanlun Xie, Wenhong Tian + 1 more
With the cutting-edge advancements in computer vision, facial expression recognition (FER) is an active research area due to its broad practical applications. It has been utilized in various fields, including education, advertising and marketing, entertainment and gaming, health, and transportation. The facial…
Hui Wei, Liping Yu, Yiran Wei
Understanding the shape and structure of objects is undoubtedly extremely important for object recognition, but the most common pattern recognition method currently used is machine learning, which often requires a large number of training data. The problem is that this kind of object-oriented learning lacks a priori…
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…
Brian Ta, Maria E. M. M. Silva, Kelly Bartlett, Umaima Afifa + 43 more
Human vision has a remarkable ability to recognize complex 3D objects such as faces that appear with any size and 3D orientations at any 3D location. If we initially memorize a face only with a normalized size and viewed from directly head on, the direct comparison between the one-sized memory and a new incoming image…
Paolo Muratore, Alireza Alemi, Davide Zoccolan
Despite their prominence as model systems to dissect visual cortical circuitry, it remains unclear whether rodents are capable of truly advanced processing of visual information. Here, we considered several psychophysical studies of rat object vision, and we used a deep convolutional neural network (CNN) to measure the…
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…
Filip Rybansky, Sadegh Rahmaniboldaji, Andrew Gilbert, Frank Guerin + 2 more
Humans recognize everyday actions without conscious effort despite challenges such as poor viewing conditions and visual similarity between actions. Yet the visual features contributing to action recognition remain unclear. To address this, we combined semantic modelling and feature reduction methods to identify…
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…
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…
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…