Results 71 to 80 of about 176,660 (282)
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
2017 International Joint Conference on Neural Networks (IJCNN), 2017 In this paper we examine learning methods combining the Random Neural Network, a biologically inspired neural network and the Extreme Learning Machine that achieve state of the art classification performance while requiring much shorter training time.
openaire +2 more sources
, 2016 Many time series are generated by a set of entities that interact with one another over time. This paper introduces a broad, flexible framework to learn from multiple inter-dependent time series generated by such entities. Our framework explicitly models the entities and their interactions through time.
Bora, Ashish +2 more
openaire +2 more sources
Dp-Rnn: Type Ii Diabetic Prediction Using Gkfcm And Rnn
Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021 Diabetes is a form of metabolic disorder marked by elevated persistent blood glucose (BG), leading to several severe problems in the long term. Continuous monitoring and prediction of BG concentration are needed to help diabetic patients maintain their wellbeing.
openaire +1 more source
Excitation Backprop for RNNs [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 CVPR 2018 Camera Ready ...
Bargal, Sarah Adel +5 more
openaire +2 more sources
Toward Environmentally Friendly Hydrogel‐Based Flexible Intelligent Sensor Systems
Advanced Intelligent Discovery, EarlyView.This review summarizes environmentally and biologically friendly hydrogel‐based flexible sensor systems focusing on physical, chemical, and physiological sensors. Furthermore, device concepts moving forward for the practical application are discussed about wireless integration, the interface between hydrogel and dry electronics, automatic data analysis
Sudipta Kumar Sarkar, Kuniharu Takei
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour +5 more
wiley +1 more source
Artificial Intelligence for Bone: Theory, Methods, and Applications
Advanced Intelligent Discovery, EarlyView.Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan +3 more
wiley +1 more source
Sensors, 2019 Accurate crop classification is the basis of agricultural research, and remote sensing is the only effective measuring technique to classify crops over large areas.
Yingwei Sun +11 more
doaj +1 more source
Deep Learning‐Assisted Design of Mechanical Metamaterials
Advanced Intelligent Discovery, EarlyView.This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source