note

Exercise: Implementing CNNs in PyTorch | Writing Image Classification from MNIST to CIFAR-10 [Basics Part 2, Free Notebook]

This is an exercise notebook for writing networks that handle images from scratch. It is provided for free. This session covers CNNs (Convolutional Neural Networks). If you were able to write the MLP ...
science

Scalable multiplexed machine learning gas sensor chips for food classification

Here, we address this problem using carbon nanotube (CNT) field-effect transistors (FETs) in which the base device structure is lithographically fabricated before the deposition of gas-sensitive ...
marktechpost

Deep Learning Framework Showdown: PyTorch vs TensorFlow in 2025

The choice between PyTorch and TensorFlow remains one of the most debated decisions in AI development. Both frameworks have evolved dramatically since their inception, converging in some areas while ...
IEEE

Comparative Analysis of TensorFlow and PyTorch for Image Classification Using CNN with Parallelism Strategies

Abstract: With an emphasis on convolutional neural networks (CNNs), this research does a thorough analysis of the effectiveness and suitability of the TensorFlow and PyTorch frameworks for image ...
IEEE

Medicinal Plant Identification Using CNN and Pytorch Lightning

Abstract: Medicinal plants have long been integral to healthcare, providing natural therapeutic compounds. With the growing interest in alternative medicine, accurate identification of these plants is ...
KDnuggets

Building a Convolutional Neural Network with PyTorch

A Convolutional Neural Network (CNN or ConvNet) is a deep learning algorithm specifically designed for tasks where object recognition is crucial - like image classification, detection, and ...
Hacker

Binary Classification: Understanding Activation and Loss Functions with a PyTorch Example

The basic principles required to solve classification tasks with neural networks are used as building blocks in more complicated deep learning problems such as object detection and instance ...
KDnuggets

A Practical Guide to Transfer Learning using PyTorch

Transfer learning is a large and growing field and this article covers just a few of its aspects. However, there are many deep learning online communities which discuss transfer learning. For example, ...
GitHub

cnn-image-classification

This project consists of following steps: - dataset creation with web scraping (BeautifulSoup) - data pre-processing (DifPy, Rembg, Keras) - CNN deep learning model training (used MobileNet V2 model) ...
Frontiers

Wheat Spike Blast Image Classification Using Deep Convolutional Neural Networks

Wheat blast is a threat to global wheat production, and limited blast-resistant cultivars are available. The current estimations of wheat spike blast severity rely on human assessments, but this ...
Analytics India Magazine

Top 8 Books To Learn Convolutional Neural Networks

Yann Lecun's development of the first convolutional neural network revolutionised computer vision and artificial intelligence. CNNs analyse images by dividing them into sections, similar to how the ...