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Python neural network for multiclass classification using softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by ...
Hosted on MSN

Network in Network (NiN) Explained – Deep Neural Network Tutorial with PyTorch

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...
IEEE

SCALES: Boost Binary Neural Network for Image Super-Resolution with Efficient Scalings

Abstract: Deep neural networks for image super-resolution (SR) have demonstrated superior performance. However, the large memory and computation consumption hinders their deployment on ...
C&EN

Leveraging Deep Learning to Address Diagnostic Challenges with Insufficient Image Data

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In recent AI-driven disease diagnosis, the success of models has depended mainly on ...
Phys.org

Researchers develop neural network for large-scale celestial object classification

A new study led by researchers from the Yunnan Observatories of the Chinese Academy of Sciences has developed a neural network-based method for large-scale celestial object classification, according ...
INSPIRE

Exploring quantum neural networks for binary classification on MNIST dataset: A swap test approach

In this study, we propose a novel modularized Quantum Neural Network (mQNN) model tailored to address the binary classification problem on the MNIST dataset. The mQNN organizes input information using ...
IEEE

Binary Neural Networks With Feature Information Retention for Efficient Image Classification

Abstract: Although binary neural networks (BNNs) enjoy extreme compression ratios, there are significant accuracy gap compared with full-precision models. Previous works propose various strategies to ...
Frontiers

Detection of weeds in vegetables using image classification neural networks and image processing

Weed management presents a major challenge to vegetable growth. Accurate identification of weeds is essential for automated weeding. However, the wide variety of weed types and their complex ...
Frontiers

Pruning and optimization of optical neural network as a binary optical trigger

Optical neural networks implemented with Mach-Zehnder Interferometer (MZI) arrays are a promising solution to enable fast and energy-efficient machine learning inference, yet finding a practical ...