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Found 6 papers, 2 papers with code
A Hybrid Deep Learning Model-based Remaining Useful Life Estimation for Reed Relay with Degradation Pattern Clustering
To provide accurate remaining useful life (RUL) estimation for reed relay, a hybrid deep learning network with degradation pattern clustering is proposed based on the following three considerations.
Time-Series Regeneration with Convolutional Recurrent Generative Adversarial Network for Remaining Useful Life Estimation
Out of this consideration, an enhanced RUL framework focusing on data self-generation is put forward for both non-cyclic and cyclic degradation patterns for the first time.
Cluster Pruning: An Efficient Filter Pruning Method for Edge AI Vision Applications
Even though the Convolutional Neural Networks (CNN) has shown superior results in the field of computer vision, it is still a challenging task to implement computer vision algorithms in real-time at the edge, especially using a low-cost IoT device due to high memory consumption and computation complexities in a CNN.
DCASE 2018 Challenge: Solution for Task 5
To address Task 5 in the Detection and Classification of Acoustic Scenes and Events (DCASE) 2018 challenge, in this paper, we propose an ensemble learning system.
Temporal Convolutional Memory Networks for Remaining Useful Life Estimation of Industrial Machinery
This paper, introduces a system model that incorporates temporal convolutions with both long term and short term time dependencies.
RF-Based Direction Finding of UAVs Using DNN
This paper presents a sparse denoising autoencoder (SDAE)-based deep neural network (DNN) for the direction finding (DF) of small unmanned aerial vehicles (UAVs).
