History of Convolutional Neural Networks for Image Classification (1989-present) | by Avishek Biswas | June, 2024
A visual tour of the greatest innovations in Deep Learning and Computer Vision.Before CNNs, the standard way to train a ...
Tag: Convolutional
Kolmogorov-Arnold Convolutional Networks (Convolutional KANs): An Innovative Alternative to Standard Convolutional Neural Networks (CNN)
Computer vision, one of the main areas of artificial intelligence, focuses on allowing machines to interpret and understand visual data. ...
Vision Transformers (ViT) vs. Convolutional Neural Networks (CNN) in AI Image Processing
Vision transformers (ViT) and convolutional neural networks (CNN) have become key players in image processing in the competitive landscape of ...
OA-CNN: A family of networks that integrates a lightweight module to greatly improve the adaptability of sparse convolutional neural networks (CNN) at minimal computational cost
In the realm of 3D scene understanding, a major challenge arises due to the irregular and sparse nature of 3D ...
Meet VMamba: An Alternative to Convolutional Neural Networks CNN and Vision Transformers to Improve Computational Efficiency
There are two main challenges in learning visual representations: the computational inefficiency of Vision Transformers (ViTs) and the limited ability ...
Meet MedGAN: a deep learning model based on Wasserstein generative adversarial networks and graph convolutional networks for the design of novel molecules
The growing urgency of innovative medicines in various medical fields, such as antibiotics, cancer treatments, autoimmune disorders, and antiviral therapies, ...
Convolutional layer: basic component of CNNs | by Egor Howell | January 2024
What are convolutional layers and how do they enable deep learning for computer vision?"https://www.flaticon.com/free-icons/neural-network" title=”neural network icons”>Neural network icons created ...
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