EEG Visual Classification Algorithm Based on Improved StackCNN Network

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EEG Visual Classification Algorithm Based on Improved StackCNN Network and Ensemble Learning Yang Qing1,2,3, Wang Yaqun1,2,3, Wen Dou1,2,3, Wang Ying1,2,3, Wang Xiangyu1,2,3 1. Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University; 2. School of Computer Science, Central China Normal University; 3. National Language Resources Monitoring and Research Network Media Center, Central … Read more

Deep Reconstruction: Image Reconstruction Based on Deep Learning

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Deep Reconstruction: Image Reconstruction Based on Deep Learning

Deep Reconstruction Professor Zhang Yi, a doctoral supervisor from Sichuan University, once introduced the basic principles and classic methods of CT reconstruction, as well as the principles and current status of CT reconstruction. In this issue, he will take us to learn about his latest IEEE TMI paper on CT reconstruction using deep learning, which … Read more

BiTCN: Multivariate Time Series Forecasting with Convolutional Networks

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BiTCN: Multivariate Time Series Forecasting with Convolutional Networks

Source: DeepHub IMBA This article is about 3300 words, suggested reading time is 10 minutes. This article will introduce the BiTCN model, which utilizes two Temporal Convolutional Networks (TCN) to encode past and future covariates while maintaining computational efficiency. In the field of time series forecasting, model architecture often relies on Multi-Layer Perceptron (MLP) or … Read more

Conformer: A Hybrid CNN-Transformer Model for Improved Feature Representation

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Conformer: A Hybrid CNN-Transformer Model for Improved Feature Representation

Follow our public account to discover the beauty of CV technology 0 Introduction In Convolutional Neural Networks (CNN), convolution operations excel at extracting local features, but there are certain limitations in capturing global feature representations. In Vision Transformers, cascading self-attention modules can capture long-range feature dependencies but tend to overlook the details of local features. … Read more

Overview of Various Convolution Operations in CNNs

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Overview of Various Convolution Operations in CNNs

Are you a new friend? Remember to click the blue text to follow me~ The official account has changed its push rules, remember to click “Looking” after reading~ Next time a new article will appear in your subscription list in a timely manner Author | Captain Note | The official account is responsible for pushing … Read more

Practical Summary of CNN Tuning

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Practical Summary of CNN Tuning

Click on the above “Beginner Learning Vision“, select to add “Star” or “Top“ Essential insights delivered promptly Reprinted from: Author | Charlotte Source | Deep Learning Enthusiasts Editor | Jishi Platform Summary of tuning techniques, all about CNN optimization. Summary of CNN Optimization Systematic evaluation of CNN advances on the ImageNet Using ELU non-linearity without … Read more

Facial Emotion Recognition Using CNN

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Facial Emotion Recognition Using CNN

Click the above “Beginner Learning Visuals“, select Star or Pin“ Heavyweight resources delivered instantly Facial expressions are an important way of communication among humans. In artificial intelligence research, deep learning techniques have become a powerful tool to enhance human-computer interaction. The analysis and assessment of facial expressions and emotions in psychology involves evaluating the predictions … Read more

Crop Disease Detection Using Image Processing and CNN

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Crop Disease Detection Using Image Processing and CNN

Click on the "Xiaobai Learns Vision" above, select "Star" or "Top" Heavyweight content delivered first time Here, we will discuss the detection of crop disease severity using OpenCV image processing techniques. This process does not involve any training part. Based on color segmentation technology, we only extract healthier plant areas and calculate disease severity based … Read more

Understanding Applications of Deep Learning in Computer Vision

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Understanding Applications of Deep Learning in Computer Vision

Source: New Machine Vision Originally from: Chengmai Technology Abstract: This article mainly introduces the five major technologies in computer vision, which are image classification, object detection, object tracking, semantic segmentation, and instance segmentation. Each technology is given a basic concept and corresponding typical methods, making it simple and easy to read. Computer vision is one … Read more

Cactus Image Classification Based on Convolutional Neural Networks (CNN)

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Cactus Image Classification Based on Convolutional Neural Networks (CNN)

Click the top“Beginner Learning Vision” to select “Star” or “Top” Heavyweight content delivered at the first time Today our goal is to build a classifier that classifies images as “cactus” or “non-cactus”. 01. Dataset This classification problem is one of the Kaggle challenges. The goal is to build a classifier that classifies images as “cactus” … Read more