1D CNN

Handwritten Digit Recognition and Application Based on TensorFlow Deep Learning

by
Handwritten Digit Recognition and Application Based on TensorFlow Deep Learning

Abstract: Handwritten digit recognition is an important component of artificial intelligence recognition systems. Due to individual differences in handwritten digits, the accuracy of existing recognition systems is relatively low. This paper completes the recognition and application of handwritten digits based on the TensorFlow deep learning framework. First, the TensorFlow deep learning framework is established, and … Read more

Illustrated Guide to Deep Learning with TensorFlow: Introduction, Principles, and Advanced Practice

by
Illustrated Guide to Deep Learning with TensorFlow: Introduction, Principles, and Advanced Practice

During the learning process, I collected relevant flowcharts for each chapter of the book “Deep Learning with TensorFlow: Introduction, Principles, and Advanced Practice.” This makes the knowledge points in the book more intuitive and easier for readers to learn and review. The flowcharts were compiled by a team I encountered before, known as the Code … Read more

Introduction to GER-UNet Model in TensorFlow

by

Today, I will share the improved model GER-UNet, which is based on the 2020 paper “Beyond CNNs: Exploiting Further Inherent Symmetries in Medical Images for Segmentation.” By understanding the ideas behind this model, similar improvements can be made based on VNet. 1. Limitations of Conventional Convolutional Networks 1. Conventional convolutional neural networks can only utilize … Read more

Introduction to DC-UNet: An Improved Model of UNet

by

Today, I will share the improved model DC-UNet, which is based on the U-Net architecture. The improvement comes from the 2020 paper titled “DC-UNet: Rethinking the U-Net Architecture with Dual Channel Efficient CNN for Medical Images Segmentation.” By understanding the concept of this model, similar improvements can be made based on VNet. 1. Original UNet … Read more

Image Recognition Based on TensorFlow and Keras

by
Image Recognition Based on TensorFlow and Keras

Click on the above“Beginner Learning Vision” to choose to addStar or “Pin” Important content delivered at the first time Introduction One of the most common uses of TensorFlow and Keras is image recognition/classification. Through this article, you will learn how to achieve this using Keras. Definition If you do not understand the basic concepts of … Read more

Implementing Checkpoint Resume Training with PyTorch

by
Implementing Checkpoint Resume Training with PyTorch

Click the above “Beginner’s Guide to Vision” and choose to add a Star or “Top” Essential content delivered promptly Introduction This article summarizes important points to consider when implementing checkpoint resume training with PyTorch, along with detailed code explanations. Recently, while trying to train a classification problem using CIFAR10, I found that the dataset is … Read more

Top 10 Deep Learning Models

by
Top 10 Deep Learning Models

Approximately 10,000 words, recommended reading time: 15 minutes. This article shares the top 10 models in deep learning, which hold significant positions in terms of innovation, application value, and impact. Since the concept of deep learning was proposed in 2006, nearly 20 years have passed. Deep learning, as a revolution in the field of artificial … Read more

Synthesia Offers Professional-Level ADR Services Based on GAN

by
Synthesia Offers Professional-Level ADR Services Based on GAN

Synthesia recently released its “Native Dubbing” technology in collaboration with the BBC, which can seamlessly replace the facial expressions and lip movements of hosts or actors, addressing existing issues in video translation and Automated Dialogue Replacement (ADR). Synthesia aims to eliminate language barriers in video content, allowing producers and users to enjoy video content in … Read more

Overview of CNN Convolution Methods

by
Overview of CNN Convolution Methods

Click the above “Beginner Learning Vision” to choose to add “Starred” or “Pinned“ Important content delivered at the first time The Essence of Convolution Conventional Convolution Single-channel Convolution Multi-channel Convolution 3D Convolution Transposed Convolution 1×1 Convolution Depthwise Separable Convolution Dilated Convolution The Essence of Convolution Before introducing various convolutions, it is necessary to revisit the … Read more

Long-Term ENSO Forecasting Using Hybrid CNN and Transformer Models

by
Long-Term ENSO Forecasting Using Hybrid CNN and Transformer Models

Click the blue text Follow us Cite this article: Lyu, P. M., T. Tang, F. H. Ling, J.-J. Luo, N. Boers, W. L. Ouyang, and L. Bai, 2024: ResoNet: Robust and Explainable ENSO Forecasts with Hybrid Convolution and Transformer Networks. Adv. Atmos. Sci., https://doi.org/10.1007/s00376-024-3316-6 Download: http://www.iapjournals.ac.cn/aas/en/article/doi/10.1007/s00376-024-3316-6 AI Special Issue | Pre-Publication Long-Term ENSO Forecasting Using … Read more