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Found 9 papers, 1 papers with code
A Novel Field-Free SOT Magnetic Tunnel Junction With Local VCMA-Induced Switching
By integrating the local voltage-controlled magnetic anisotropy (VCMA) effect, Dzyaloshinskii-Moriya interaction (DMI) effect, and spin-orbit torque (SOT) effect, we propose a novel device structure for field-free magnetic tunnel junction (MTJ).
ST-ReGE: A Novel Spatial-Temporal Residual Graph Convolutional Network for CVD
When applying DL models, ECG signals are usually treated as synchronized signals arranged in Euclidean space, which is the abstraction and generalization of real space.
A Latent Encoder Coupled Generative Adversarial Network (LE-GAN) for Efficient Hyperspectral Image Super-resolution
To alleviate the problem of mode collapse, this work has proposed a novel GAN model coupled with a latent encoder (LE-GAN), which can map the generated spectral-spatial features from the image space to the latent space and produce a coupling component to regularise the generated samples.
Generative Adversarial Network
Hyperspectral Image Super-Resolution
+1
A Novel CropdocNet for Automated Potato Late Blight Disease Detection from the Unmanned Aerial Vehicle-based Hyperspectral Imagery
Late blight disease is one of the most destructive diseases in potato crop, leading to serious yield losses globally.
A Biologically Interpretable Two-stage Deep Neural Network (BIT-DNN) For Vegetation Recognition From Hyperspectral Imagery
Spectral-spatial based deep learning models have recently proven to be effective in hyperspectral image (HSI) classification for various earth monitoring applications such as land cover classification and agricultural monitoring.
Fully Memristive Neural Network Merging Image Preprocessing and Pattern Recognition
With the development of research on novel memristor model and device, fully memristive neural networks have become a hot research topic recently.
Emerging Technologies
The MBPEP: a deep ensemble pruning algorithm providing high quality uncertainty prediction
In this paper, a margin-based Pareto deep ensemble pruning (MBPEP) model is proposed.
Fully Memristive Spiking-Neuron Learning Framework and its Applications on Pattern Recognition and Edge Detection
In this paper, a fully memristive spiking-neuron learning framework is introduced, in which a neuron structure is just built of one drift and one diffusion memristive models.
Emerging Technologies
A Hardware Friendly Unsupervised Memristive Neural Network with Weight Sharing Mechanism
Memristive neural networks (MNNs), which use memristors as neurons or synapses, have become a hot research topic recently.
