Results 81 to 90 of about 212,585 (307)
Few-Shot-BERT-RNN Narrative Structure Analysis for Andersen's Stories
JOIV: International Journal on Informatics VisualizationEvent Extraction (EE) is a pivotal task for NLP, where important events in the narrative text need to be detected and recognized. We present an alternative method for extracting events from Hans Christian Andersen's fairy tales, utilizing Few-Shot ...
Erna Daniati +3 more
doaj +1 more source
PREDICTING MEDICINE DEMAND USING DEEP LEARNING TECHNIQUES
Iraqi Journal for Computers and Informatics, 2023 Medication supply and storage are essential components of the medical industry and distribution. Most medications have a predetermined expiration date. When the demand is met in large quantities that exceed the actual need, this leads to the accumulation
Bashaer Abdurahman Mousa +1 more
doaj
Context-aware Sequential Recommendation
, 2016 Since sequential information plays an important role in modeling user behaviors, various sequential recommendation methods have been proposed. Methods based on Markov assumption are widely-used, but independently combine several most recent components ...
Li, Zhaokang +4 more
core +1 more source
, 2021 Previous works on the Recurrent Neural Network-Transducer (RNN-T) models have shown that, under some conditions, it is possible to simplify its prediction network with little or no loss in recognition accuracy (arXiv:2003.07705 [eess.AS], [2], arXiv:2012.06749 [cs.CL]). This is done by limiting the context size of previous labels and/or using a simpler
Botros, Rami +5 more
openaire +2 more sources
Advanced Science, EarlyView.A neuromorphic computing platform using spin‐orbit torque‐controlled magnetic textures is reported. The device implements bio‐inspired synaptic functions and achieves high performance in both pattern recognition (>93%) and combinatorial optimization (>95%), enabling unified processing of cognitive and optimization tasks.
Yifan Zhang +13 more
wiley +1 more source
, 2017 Sustainability of the global environment is dependent on the accurate land cover information over large areas. Even with the increased number of satellite systems and sensors acquiring data with improved spectral, spatial, radiometric and temporal ...
Liu, Xiuwen +2 more
core +1 more source
Advanced Science, EarlyView.Computational annotation of various tissue types in heterogeneous samples such as colorectal cancer liver metastasis (CRLM) using spatial autocorrelation analysis on non‐destructive mid‐infrared (MIR) imaging data enabled correlative multimodal mass spectrometry imaging (MSI) for spatial investigation of lipid tumor marker candidates. The method can be
Miriam F. Rittel +12 more
wiley +1 more source
Character-Level Incremental Speech Recognition with Recurrent Neural Networks
, 2016 In real-time speech recognition applications, the latency is an important issue. We have developed a character-level incremental speech recognition (ISR) system that responds quickly even during the speech, where the hypotheses are gradually improved ...
Hwang, Kyuyeon, Sung, Wonyong
core +1 more source
Deep Learning for Household Load Forecasting—A Novel Pooling Deep RNN
IEEE Transactions on Smart Grid, 2018 The key challenge for household load forecasting lies in the high volatility and uncertainty of load profiles. Traditional methods tend to avoid such uncertainty by load aggregation (to offset uncertainties), customer classification (to cluster ...
Heng Shi, Minghao Xu, Ran Li
semanticscholar +1 more source
Nanozymes Integrated Biochips Toward Smart Detection System
Advanced Science, EarlyView.This review systematically outlines the integration of nanozymes, biochips, and artificial intelligence (AI) for intelligent biosensing. It details how their convergence enhances signal amplification, enables portable detection, and improves data interpretation.
Dongyu Chen +10 more
wiley +1 more source