This project is a Deep Learning-based Medical Imaging Platform designed to assist clinicians and researchers in analyzing wound images. It combines state-of-the-art Convolutional Neural Networks (CNNs) for multi-class classification with Vector Similarity Sear…
This study proposes a novel approach that combines theory and data-driven choice models using Artificial Neural Networks (ANNs). In particular, we use continuous vector representations, called embeddings, for encoding categorical or discrete explanat...
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In this article, we report a vector-network-analyzer-free and real-time LC wireless capacitance readout system based on perturbed nonlinear parity-time (PT) symmetry. The system is composed of two inductively coupled reader-sensor parallel RLC resona...
We introduce COMBO - a fully neural NLP system for accurate part-of-speech tagging, morphological analysis, lemmatisation, and (enhanced) dependency parsing. It predicts categorical morphosyntactic features whilst also exposes their vector representa...
In this paper, authors want to comment on a recently published article describing the Mathematical Modeling of Current Source Matrix Converter (CSMC) with two modulation strategies, namely: Venturini and Space Vector Modulation (SVM). Reported flaws...
A professional high-resolution die-cut sticker design for a travel suitcase. The subject is [INSERT SUBJECT, e.g., a majestic mountain range with a compass rose and a vintage airplane flying overhead]. Style: Vibrant flat vector art with bold, clean lines and…
Multi-vector late-interaction retrievers such as ColBERT achieve state-of-the-art retrieval quality, but their query-time cost is dominated by exhaustively computing token-level MaxSim interactions for every candidate document. While approximating la...
state-of-the-art search over vector embeddings and structured data (SIGMOD '24) (⭐ 104)
In this survey of the Andersen-Lempert theory we present the state of the art in the study of the density property (which means that the Lie algebra generated by completely integrable holomorphic vector fields on a given Stein manifold is dense in th...
Time series classification holds broad application value in communications, information countermeasures, finance, and medicine. However, state-of-the-art (SOTA) methods-including HIVE-COTE, Proximity Forest, and TS-CHIEF-exhibit high computational co...
Additive composition (Foltz et al, 1998; Landauer and Dumais, 1997; Mitchell and Lapata, 2010) is a widely used method for computing meanings of phrases, which takes the average of vector representations of the constituent words. In this article, we...
In this paper, it is first discovered that EcN has natural magnetically controlled properties, that is, E coli Nissle 1917 cells move in a gradient magnetic field of permanent magnets without artificial magnetic labeling. It is also shown in the pape...
Conditional random field (CRF) and Structural Support Vector Machine (Structural SVM) are two state-of-the-art methods for structured prediction which captures the interdependencies among output variables. The success of these methods is attributed t...
A compatible associative algebra is a vector space equipped with two associative multiplication structures that interact in a certain natural way. This article presents the classification of these algebras with dimension less than four, as well as th...
Fork of Duane Merrill Merge-based Parallel Sparse Matrix-Vector Multiplication Artifact (⭐ 6)
Let ${\mathbb F}_0$ be an algebraically closed field, with $char({\mathbb F}_0)=0$. In this article, for prime numbers $p\geq 2$, we construct smooth affine algebras $B$ over ${\mathbb F}_0$, with $\dim B=p+2$. Further, we construct projective $B$-mo...
In this paper, we propose a novel method for the prior-art search task. We fine-tune SciBERT transformer model using Triplet Network approach, allowing us to represent each patent with a fixed-size vector. This also enables us to conduct efficient ve...