27 papers · ranked by Valyu relevance
А. М. Михайлов, Mikhail Karavay
Artificial neural networks use a lot of coefficients that take a great deal of computing power for their adjustment, especially if deep learning networks are employed. However, there exist coefficients-free extremely fast indexing-based technologies that work, for instance, in Google search engines, in genome…
Alexandre Benatti, Luciano da Fontoura Costa
Pattern recognition constitutes a particularly important task underlying a great deal of scientific and technologica activities. At the same time, pattern recognition involves several challenges, including the choice of features to represent the data elements, as well as possible respective transformations. In the…
Masoud Amiri, Amir Homayoun Jafari, Bahador Makkiabadi, Soheila Nazari
'Soheila Nazari'] Artificial intelligence computing adapted from biology is a suitable platform for the development of intelligent machines by imitating the functional mechanisms of the nervous system in creating high-level activities such as learning, decision making and cognition in today's systems. Here, the…
Oskar H Schnaack, Luca Peliti, Armita Nourmohammad
Keeping a memory of evolving stimuli is ubiquitous in biology, an example of which is immune memory for evolving pathogens. However, learning and memory storage for dynamic patterns still pose challenges in machine learning. Here, we introduce an analytical energy-based framework to address this problem. By accounting…
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…
Min Wang, Xuefei Yin, Yanming Zhu, Jiankun Hu
Cognitive biometrics is an emerging branch of biometric technology. Recent research has demonstrated great potential for using cognitive biometrics in versatile applications, including biometric recognition and cognitive and emotional state recognition. There is a major need to summarize the latest developments in this…
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…
Mario Stepanik
This paper introduces a novel unsupervised learning paradigm inspired by Gerald Edelman's theory of neuronal group selection ("Neural Darwinism"). The presented automaton learns to recognize arbitrary symbols (e.g., letters of an alphabet) when they are presented repeatedly, as they are when children learn to read. On…
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…
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…
Mélina Baheux Blin, Vincent Loreau, Frank Schnorrer, Pierre Mangeol
Regular spatial patterns are ubiquitous forms of organization in nature. In animals, regular patterns can be found from the cellular scale to the tissue scale, and from early stages of development to adulthood. To understand the formation of these patterns, how they form and mature, and how they are affected by…
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…
Svetlana Volotsky, Ohad Ben-Shahar, Opher Donchin, Ronen Segev
Recognition of individual objects and their categorization is a complex computational task. Nevertheless, visual systems can 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 different…
Yaoyao Yun, Jianwen Xu
In recent years, sparse sampling techniques based on regression analysis have witnessed extensive applications in face recognition research. Presently, numerous sparse sampling models based on regression analysis have been explored by various researchers. Nevertheless, the recognition rates of the majority of these…
Mehta, Diksha, Mehta, Prateek
Handwritten character recognition is getting popular among researchers because of its possible applications in facilitating technological search engines, social media, recommender systems, etc. The Devanagari script is one of the oldest language scripts in India that does not have proper digitization tools. With the…
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…
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…
Jitka Poměnková, Tobiáš Malach, Loris Nanni
Face recognition has become an integral part of modern security processes. This paper introduces an optimization approach for the quantile interval method (QIM), a promising classifier learning technique used in face recognition to create face templates and improve recognition accuracy. Our research offers a three-fold…
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…
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…
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…
Krishnendu K. S
—With the tremendous advancements in face recognition technology, face modality has been widely recognized as a significant biometric identifier in establishing a person's identity rather than any other biometric trait like fingerprints that require contact sensors. However, due to inter-class similarities and…
Rishabh Raj, Dar Dahlen, Kyle Duyck, C. Ron Yu
Sensory inputs conveying information about the environment are often noisy and incomplete, yet the brain can achieve remarkable consistency in recognizing objects. Presumably, transforming the varying input patterns into invariant object representations is pivotal for this cognitive robustness. In the classic…
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…