In this tutorial, we take a hands-on approach to building an advanced convolutional neural network for DNA sequence classification. We focus on simulating real biological tasks, such as promoter ...

1 Institute of Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia 2 Department of Learning, Data Analytics and Technology, Section Cognition, Data and ...

Computational optics represents a shift in approach where optical hardware and computational algorithms are designed to work together, enabling imaging capabilities that surpass those of traditional ...

ABSTRACT: With the development of unmanned aerial vehicle (UAV) LiDAR technology, large-scale high-precision point cloud data is gradually playing an important role in the classification and ...

As she sang on the song “exile”: “I gave so many signs.” But did she? Did Taylor Swift hint that The Life of a Showgirl, her just-announced 12th studio album, was imminent, or were the fan theories ...

As an essential branch of chemical science, biochemical analysis is widely applied in disease diagnosis, food safety testing, environmental monitoring, and other fields. Artificial intelligence (AI) ...

Abstract: We apply the innovations method to Viterbi decoding of convolutional codes. First, we calculate the covariance matrix of the innovation (i.e., the soft-decision input to the main decoder in ...

Introduction: Seismic first break (FB) picking helps us with near surface tomography, microseismic detection among other tasks. Using image semantic segmentation (ISS) networks to do so has been a hot ...

We propose an end-to-end deep neural encoder-decoder model to encode and decode brain activity in response to naturalistic stimuli using functional magnetic resonance imaging (fMRI) data. Leveraging ...

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