23 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…
Muhammad Furqan Afzal, Christian David Márton, Erin L. Rich, Kanaka Rajan
Neuroscience has seen a dramatic increase in the types of recording modalities and complexity of neural time-series data collected from them. The brain is a highly recurrent system producing rich, complex dynamics that result in different behaviors. Correctly distinguishing such nonlinear neural time series in…
Osvaldo Velazquez-Gonzalez, Antonio Alarcón-Paredes, Cornelio Yañez-Marquez
Classification is a central task in machine learning, underpinning applications in domains such as finance, medicine, engineering, information technology, and biology. However, machine learning pattern classification can become a complex or even inexplicable task for current robust models due to the complexity of…
Su Yang, Sanaul Hoque, Farzin Deravi, Christophoros Nikou
A novel instance-based algorithm for pattern classification is presented and evaluated in this paper. This new method is motivated by the challenge of pattern classifications where only limited and/or noisy training data are available. For every classification, the proposed system transforms the query data and the…
Mohd Anjum, Sana Shahab, Shabir Ahmad, Sami Dhahbi + 1 more
The input image and clinical data are jointly analyzed for pattern identification. The is analyzed for and classifications for preventing error overlaps. Considering the patterns used, the training and analysis are separated for correlation. This correlation identifies (from similar) and CE from for further analysis…
Christian Lovis, Dian Hu, Mikko Nuutinen, Azizollah Arbabisarjou + 6 more
Background It is important to exploit all available data on patients in settings such as intensive care burn units (ICBUs), where several variables are recorded over time. It is possible to take advantage of the multivariate patterns that model the evolution of patients to predict their survival. However, pattern…
Pauline Rothmann-Brumm, Steven L. Brunton, Isabel Scherl
formation in gravure printing Authors: ['Pauline Rothmann-Brumm' 'Steven L. Brunton' 'Isabel Scherl'] Hydrodynamic pattern formation phenomena in printing and coating processes are still not fully understood. However, fundamental understanding is essential to achieve high-quality printed products and to tune printed…
Ahmed Bouziane, Ala Eddine Boudemia, Taib Abderaouf Bourega, Mahdjoub Hamdi
Histopathological analysis of whole-slide images is the gold standard technique for diagnosis of lung cancer and classifying it into types and subtypes by specialized pathologists. This labor-based approach is time and effort consuming, which led to development of automatic approaches to assist in reducing the time and…
Yao Chen, Wensheng Gan, Yongdong Wu, Philip S. Yu
Contrast pattern mining (CPM) is an important and popular subfield of data mining. Traditional sequential patterns cannot describe the contrast information between different classes of data, while contrast patterns involving the concept of contrast can describe the significant differences between datasets under…
Juan Li, Cai Dai
The unceasing increase of data quantity severely limits the wide application of mature classification algorithms due to the unacceptable execution time and the insufficient memory. How to fast incrementally obtain high decision reference set and adapt to incremental data environment is urgently needed in incremental…
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…
Kavya Singh, Anil Kumar Koundal, Navjeet Kaur
The visual descriptor methods like Local Binary Pattern (LBP) capture anatomical structures in captured images along with their disparities, which can be exploited by suitable methods for the diagnosis of medical anomalies. We developed a Local Mean Gradient Pattern (LMGP), based partly on LBP, a feature extraction…
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…
Purbarag Pathak Choudhury, Ujjal Kr Dutta, Dhruba K. Bhattacharyya
—A satellite image is a remotely sensed image data, where each pixel represents a specific location on earth. The pixel value recorded is the reflection radiation from the earth's surface at that location. Multispectral images are those that capture image data at specific frequencies across the electromagnetic spectrum…
Authors not listed
Chemical reactions typically follow mechanistic templates and hence fall into a manageable number of clearly distinguishable classes that usually labeled by names of chemists who discovered or explored them. These ``named reactions'' form the core of reaction ontologies and are associated with specific synthetic…
Abhijit Sen, Giridas Maiti, Bikram Kumar Parida, Mishra + 3 more
—Feature engineering continues to play a critical role in image classification, particularly when interpretability and computational efficiency are prioritized over deep learning models with millions of parameters. In this study, we revisit classical machine learning based image classification through a novel approach…
Ping Yang, E. Adrian Henle, Cory M. Simon, Xiaoli Fern
Pesticides benefit agriculture by increasing crop yield, quality, and security. However, pesticides may inadvertently harm bees, which are valuable as pollinators. Thus, candidate pesticides in development pipelines must be assessed for toxicity to bees. Leveraging a data set of 382 molecules with toxicity labels from…
Maryam Eshraghi Evari, Md. Nasir Sulaiman, Amir Behjat
Data Authors: ['Maryam Eshraghi Evari' 'Md. Nasir Sulaiman' 'Amir Behjat'] DNA microarray gene-expression data has been widely used to identify cancerous gene signatures. Microarray can increase the accuracy of cancer diagnosis and prognosis. However, analyzing the large amount of gene expression data from microarray…
Suri Dipannita Sayeed, Jan Niclas Wolf, Ina Koch, Guang Song
Protein fold classification reveals key structural information about proteins that is essential for understanding their function. While numerous approaches exist in the literature that classifies protein fold from sequence data using machine learning, there is hardly any approach that classifies protein fold from the…
Denice van Herwerden, Jake O'Brien, Phil Choi, Kevin Thomas + 2 more
Isotopologue identification or removal is a necessary step to reduce the number of features that need to be identified in samples analyzed with non-targeted analysis. Currently available approaches rely on either predicted isotopic patterns or an arbitrary mass tolerance, requiring information on the molecular formula…
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…
Authors not listed
This research delves into olfaction, a sensory modality that remains complex and inadequately understood. We aim to fill in two gaps in recent studies that attempted to use machine learning and deep learning approaches to predict human smell perception. The first one is that molecules are usually represented with…
Trevor Gokey, David L. Mobley
Molecular mechanics force fields require a chemical perception model to assign parameters to molecules. A recent advancement in force fields is the use of the SMARTS substructure query language as the perception model. Although it is straightforward to write SMARTS patterns to define new force field parameters, it is…