IEEE

Multi-Dimensional Recurrent Neural Networks Hyperspectral image classification

Abstract: Classifying hyperspectral images (HSIs) is a top priority for the remote sensing field. Discriminative feature extraction of HSI using conventional ML techniques is difficult because of the ...
eLife

A differentiable model for optimizing the genetic drivers of synaptogenesis

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...
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GRU explained | How gated recurrent units work

Gated Recurrent Unit (GRU) is a type of Recurrent Neural Network (RNN) which performs better than Simple RNN while dealing with longer input data. Gated Recurrent Unit (GRU) is an advance RNN which ...
eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
IEEE

V-DCRNN: Virtual Network-Based Diffusion Convolutional Recurrent Neural Network for Estimating Unobserved Traffic Data

Abstract: Several studies have analyzed traffic patterns using Vehicle Detector (VD) and Global Positioning System (GPS) data. VD records the speed of vehicles passing through detectors, GPS data ...