25 papers · ranked by Valyu relevance
Sher Afzal Khan, Daojing He, Jose C. Valverde
Every accumulation of data in its raw form holds obscure patterns. Pattern recognition deals with the science of transforming and classifying entities on the basis of these patterns. It is a vast field as it deals with data from diverse sources. Data can be of single dimensional nature as in case of stock exchanges and…
Jonathan Roberge, Michael Castelle, Aaron Mendon-Plasek
The slow and uneven forging of a novel constellation of practices, concerns, and values that became machine learning occurred in 1950s and 1960s pattern recognition research through attempts to mechanize contextual significance that involved building “learning machines” that imitated human judgment by learning from…
Federico Holik, Giuseppe Sergioli, Héctor Freytes, A. Plastino
We present a generalization of the problem of pattern recognition to arbitrary probabilistic models. This version deals with the problem of recognizing an individual pattern among a family of different species or classes of objects which obey probabilistic laws which do not comply with Kolmogorov's axioms. We show that…
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…
Margarete Dytkowicz, Marcello Tania, Rachel Hinds, William M. Megill + 2 more
Individual recognition of animals is an important aspect of ecological sciences. Photograph-based individual recognition options are of particular importance since these represent a non-invasive method to distinguish and identify individual animals. Recent developments and improvements in computer-based approaches make…
Hongzhi Li, Joseph G. Ellis, Lei Zhang, Shih‐Fu Chang
Visual patterns represent the discernible regularity in the visual world. They capture the essential nature of visual objects or scenes. Understanding and modeling visual patterns is a fundamental problem in visual recognition that has wide ranging applications. In this paper, we study the problem of visual pattern…
Shadnaz Asgari, Fabien Scalzo, Magdalena Kasprowicz
Recent advances in data acquisition and various monitoring modalities have resulted in generating and collecting a growing volume of biological and medical data at unprecedented speed and scale [1]. These accumulated data can be utilized for a more effective delivery of care and enhanced clinical decision-making [2].…
Authors not listed
X-ray diffraction (XRD) is an immediate and powerful characterization technique that provides detailed information on the lattice structure and long-range order in crystalline materials. In recent decades, the quality and quantity of available crystal structure data has exploded, in large part due to the advent of…
Tirtharaj Dash, Tanistha Nayak
— This paper investigates a method of Handwritten English Character Recognition using Artificial Neural Network (ANN). This work has been done in offline Environment for non correlated characters, which do not possess any linear relationships among them. We test that whether the particular tested character belongs to a…
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…
M. W. Spratling
Predictive coding has been proposed as a model of the hierarchical perceptual inference process performed in the cortex. However, results demonstrating that predictive coding is capable of performing the complex inference required to recognise objects in natural images have not previously been presented. This article…
Yusuf Brima
Recognition plays a crucial role in the formation of social bonds, mate selection, kin selection and survival across species. However, a unifying framework for understanding recognition systems in biology is lacking. We, therefore, propose a theoretical framework for biological recognition utilizing basic principles…
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…
Minjoon Kouh
When an object moves smoothly across a field of view, the identify of the object is unchanged, but the activation pattern of the photoreceptors on the retina changes drastically. One of the major computational roles of our visual system is to manage selectivity for different objects and tolerance to such…
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…
Masoud Ghodrati, Karim Rajaei, Reza Ebrahimpour
It is debated whether the representation of objects in inferior temporal (IT) cortex is distributed over activities of many neurons or there are restricted islands of neurons responsive to a specific set of objects. There are lines of evidence demonstrating that fusiform face area (FFA-in human) processes information…
Netta Ollikka, Anni Bergström, Markku Kilpeläinen, Stéphane Deny
Mounting evidence suggests that recurrent processes in the visual system play a critical role during challenging recognition tasks. Backward masking techniques have traditionally been used as a non-invasive method for studying recurrent processes: A mask follows the target image, presumably disrupting ongoing…
Masoud Ghodrati, Seyed-Mahdi Khaligh-Razavi, Reza Ebrahimpour, Karim Rajaei + 2 more
'Karim Rajaei' 'Mohammad Pooyan' 'Daniel Durstewitz'] Humans can effectively and swiftly recognize objects in complex natural scenes. This outstanding ability has motivated many computational object recognition models. Most of these models try to emulate the behavior of this remarkable system. The human visual system…
Courtney J. Spoerer, Patrick McClure, Nikolaus Kriegeskorte
Feedforward neural networks provide the dominant model of how the brain performs visual object recognition. However, these networks lack the lateral and feedback connections, and the resulting recurrent neuronal dynamics, of the ventral visual pathway in the human and nonhuman primate brain. Here we investigate…
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.…
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…
Authors not listed
Recent advances in artificial intelligence have significantly improved spectral data analysis. In this study, we used unsupervised machine learning to classify chemical compounds based on infrared (IR) spectral images, without relying on prior chemical knowledge. The potential of machine learning for chemical…
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…
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
The capacity to pattern biomolecules within microfluidic devices expands the scope of microfluidic technologies. In such patterned systems, surface-bound components remained localized, while the microfluidic network supplies reagents and removes waste products. This approach has enabled continuous protein expression…