Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...
Abstract: Skin cancer ranks among ubiquitous malignancies, its prevalence escalating due to ecological shifts and protracted ultraviolet (UV)exposure. This study aims to address the pressing need for ...
Abstract: Unless diagnosed and treated early, brain tumors unusual growths may prove to be lethal. Even with the standard methods, such as MRI scans, to precisely diagnose brain cancers, it may be ...
+This project focuses on building a Convolutional Neural Network (CNN) using Keras (TensorFlow backend) to classify images into two categories: Dog and Cat. + +The objective is to learn meaningful ...
Abstract: Hyperspectral image (HSI) data have a wide range of spectral information that is valuable for numerous tasks. HSI data encounter some challenges, like insufficient representation of spectral ...
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Image classification with CNNs in Keras | Easy guide
In this video, we will implement Image Classification using CNN Keras. We will build a Cat or Dog Classification model using CNN Keras. Keras is a free and open-source high-level API used for neural ...
Abstract: This paper proposes an interpretable and accurate approach to brain tumor classification using MRI data by comparing Convolutional Neural Networks (CNNs) with Scattering Networks (ScatNet).
Abstract: Artificial intelligence algorithms like the convolutional neural network (CNN) allow automated medical image analysis. However, accurate classification of tumour tissues in histopathological ...
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