A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...
Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive technology and inclusive education. In an attempt to close that gap, I developed a ...
Abstract: This study investigates the application of Spiking Neural Network (SNN) in seismic signal denoising by developing a Convolutional Neural Network (CNN) to SNN conversion framework. We focus ...
Introduction: Rapid and scalable classification of SARS-CoV-2 genomes from spike-gene sequences can support real-time genomic surveillance in contexts where whole-genome data or high-end computing ...
Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...
Abstract: This paper introduces a groundbreaking approach to weather phenomena classification, presenting a novel deep neural network design (Resnet 50 with transfer learning). Simultaneously, we ...
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