Results 51 to 60 of about 176,660 (282)
, 2017 Recently, skeleton based action recognition gains more popularity due to cost-effective depth sensors coupled with real-time skeleton estimation algorithms.
Wang, Hongsong, Wang, Liang
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Memristive Physical Reservoir Computing
Advanced Science, EarlyView.Memristors’ nonlinear dynamics and input‐dependent memory effects make them ideal candidates for high‐performance physical reservoir computing (RC). Based on their conductance modulation, memristors can be classified as electronic or optoelectronic types.
Dian Jiao +9 more
wiley +1 more source
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
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DESIGN OF SMART TOURISM SYSTEMS TO FORECAST FOREIGN TOURIST ARRIVAL RATE USING DEEP LEARNING TECHNIQUES [PDF]
Proceedings on Engineering SciencesIndia's tourism potential is vast, driven by its rich history, diverse ecology, and extensive natural beauty. The country offers various niche tourism experiences, including cruises, adventure, medical, wellness, sports, MICE, eco-tourism, film, rural ...
Ratna Kanth Gudala +3 more
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Inter-Session Modeling for Session-Based Recommendation
, 2017 In recent years, research has been done on applying Recurrent Neural Networks (RNNs) as recommender systems. Results have been promising, especially in the session-based setting where RNNs have been shown to outperform state-of-the-art models. In many of
Langseth, Helge +2 more
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, 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 Electronic Materials, EarlyView.Physical reservoir computing (PRC) based on spin wave interference has demonstrated high computational performance, yet room for improvement remains. In this study, we fabricated this concept PRC with eight detectors and evaluated the impact of the number of detectors using a chaotic time series prediction task.
Sota Hikasa +6 more
wiley +1 more source
Compressing Recurrent Neural Network with Tensor Train
, 2017 Recurrent Neural Network (RNN) are a popular choice for modeling temporal and sequential tasks and achieve many state-of-the-art performance on various complex problems.
Nakamura, Satoshi +2 more
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Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
Advanced Electronic Materials, EarlyView.This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho +6 more
wiley +1 more source
Neural network analysis in time series forecasting
Российский технологический журналObjectives. To build neural network models of time series (LSTM, GRU, RNN) and compare the results of forecasting with their mutual help and the results of standard models (ARIMA, ETS), in order to ascertain in which cases a certain group of models ...
B. Pashshoev, D. A. Petrusevich
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