Deep learning approaches, particularly convolutional neural networks (CNNs) and other architectures, were used in 49 papers. These models excel at image-based tasks such as land cover classification, ...

In today's data-driven environment, Python has become the mainstream language in the fields of machine learning and data science due to its concise syntax, rich library support, and active community, ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

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 ...

Abstract: Quantum neural networks (QNNs) are gaining attention as a promising foundation for next-generation machine learning. However, the practical deployment of QNNs, particularly in vision tasks, ...

The authenticity of corn seeds is critical to yields and their market value. The screening of corn ears is an important step in the processing of corn seeds. In order to protect the intellectual ...

Background and objectives: This paper introduces a novel lightweight MM-3DUNet (Multi-task Mobile 3D UNet) network designed for efficient and accurate segmentation of breast cancer tumors masses from ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Raman spectroscopy in biological applications faces challenges due to complex spectra, ...

Name - - CNN - Convolution Neural Network For Photo Recognizing Goal - - Recognize Handwriting Word Photo Detail: Total 5 layers neural network * Convolution layer * Pooling layer * Input layer layer ...

Skin conditions are a worldwide health issue that requires prompt and accurate diagnosis in order to be effectively treated. This study presents a Convolutional Neural Network (CNN)-based automated ...