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 ...
Deep learning-based image steganalysis has progressed in recent times, with efforts more concerted toward prioritizing detection accuracy over lightweight frameworks. In the context of AI-driven ...
Abstract: Nowadays, Artificial Intelligence (AI) is playing a vital role in data classification. In this work, a Python library called as Keras, is used for classification of MNIS T dataset, a ...
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 ...