Abstract: Breast cancer poses lots of challenges in the medical fraternity worldwide. Hence, it requires early diagnosis to treat the affected people. In this paper, we have presented a novel Dilated ...

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 ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

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 ...

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 ...

FLAMeS, a new convolutional neural network, enhances MS lesion segmentation accuracy using only T2-weighted FLAIR images, making it more applicable in clinical settings. The algorithm outperformed ...

Introduction: Underwater acoustic (UWA) communication systems confront significant challenges due to the unique, dynamic, and unpredictable nature of acoustic channels, which are impacted by low ...

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: In the field of brain-computer interfaces (BCI), motor imagery (MI) classification is a critically important task, with the primary objective of decoding an individual's MI intentions ...

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 ...