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 ...
Abstract: A convolutional neural network (CNN)-based architecture for the optimization of demodulation reference signal (DMRS) patterns is proposed for 5G new radio systems. The proposed architecture ...
Like all AI models based on the Transformer architecture, the large language models (LLMs) that underpin today’s coding ...
Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...
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: Plant and leaf diseases have a significant impact on agricultural production, leading to a decrease in crop yield and quality. Effective crop management demands early and precise detection ...
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 ...
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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 ...
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