Click the “Visual Learning for Beginners” above, and choose to add “Star” or “Pin“ Important content delivered first-hand Introduction: The extraction of edges and contours is a very tricky task, as details may be obscured by overly strong image lines. Texture itself is a weak edge distribution pattern, and hierarchical representation is a commonly used … Read more
Click on the above “Beginner’s Visual Learning”, select to add Star or “Pinned” Heavyweight content delivered first-hand Introduction Traditional deep learning-based object detection networks often resize images during the data preprocessing stage to achieve a uniform size and scale in the feature maps. The resizing aims to facilitate model propagation and fully connected classification. However, … Read more
Click the above“Beginner’s Visual Learning”, select to addstar or “pin” Important content delivered promptly Image source: Internet Author: Huang Yu, Chief Scientist at Singularity Auto Editor: Hoh Xil Source: https://zhuanlan.zhihu.com/p/78051407 Introduction: The extraction of edges and contours is a very tricky task, as details may be obscured by overly strong image lines. Texture itself is … Read more
The dream of creating machines that imitate human intelligence has existed for a long time. Although it mostly appeared in science fiction, in recent decades, we have gradually made progress in building intelligent machines that can perform certain tasks like humans. This field is known as artificial intelligence. The origins of artificial intelligence can perhaps … Read more
↑ ClickBlue TextFollow the Jishi platformAuthor丨Pai Pai XingSource丨CVHub Jishi Introduction This article presents a simple yet efficient modern inverted residual mobile module designed for mobile applications. The proposed efficient model (Efficient MOdel, EMO) achieves excellent overall performance on the ImageNet-1K, COCO2017, and ADE20K benchmarks, surpassing the SOTA models based on CNN/Transformer at the same computational … Read more
Chromatin accessibility (open chromatin accessibility) has gained increasing attention in the context of gene regulation and evolution, but our understanding of it remains limited. There is particularly little knowledge about how chromatin accessibility develops and evolves. Recently, the Zhao Li laboratory at The Rockefeller University published a research paper titled The evolution and mutational robustness … Read more
Click the blue text above to follow us 1 Overview Source: This article optimizes the lift-to-drag ratio of airfoils using Genetic Algorithm (GA) and Simulated Annealing (SA) based on a pre-trained Convolutional Neural Network (CNN) as the evaluation function. Abstract: Airfoil shape optimization is a fundamental part of airfoil design in the field of aerodynamic … Read more
Paper Title TGTM: TinyML-based Global Tone Mapping for HDR Sensors 1 IntroductionAdvanced Driver Assistance Systems (ADAS) that rely on multiple cameras are becoming increasingly popular in vehicle technology.However, traditional imaging sensors struggle to capture clear images in conditions with strong lighting contrasts, such as at the exit of tunnels, due to their limited dynamic range.Introducing … Read more
Title: A synergistic CNN-transformer network with pooling attention fusion for hyperspectral image classification Paper Link: https://github.com/chenpeng052/SCT-Net Twin-Branch Feature Extraction Module (TBFE): Parallel combination of3D Convolution (for spectral features) and2D Convolution (for spatial features), achieving spectral-spatial joint modeling early on. Hybrid Pooling Attention Module (HPA): Combines average pooling and max pooling to capture spatial dependencies through … Read more
Title: A synergistic CNN-transformer network with pooling attention fusion for hyperspectral image classification Paper link: https://github.com/chenpeng052/SCT-Net HPA (Hybrid Pooling Attention) Hybrid Pooling Attention: Divides channels into groups and performs global average pooling and global max pooling in both horizontal and vertical directions, followed by a 1×11 imes11×1 convolution and Sigmoid to obtain channel attention; simultaneously, … Read more