Adaptive Sparse Convolutional Networks with Global Context Enhancement for Faster Object Detection on Drone Images * Authors: [[Bowei Du]], [[Yecheng Huang]], [[Jiaxin Chen]], [[Di Huang]] 初读印象 comment:: 提出了一种新型全局上下文增强自适应稀疏卷积网络(CEASC)。首先开发了一个上下文增强组归...
This study proposes the use of adaptive sparse convolutional networks based on class maps for real-time onboard detection in UAV-RS images (SCCMDet) to solve this problem. For data pre-processing, SCCMDet obtains the real class maps as labels from the ground truth to supervise the ...
Convolutional sparse codingConvolutional neural networkAdaptiveThe convolutional sparse coding-based super-resolution (CSC-SR) method has shown its good performance in single image super-resolution. It divides the low-resolution (LR) image into low-frequency part and the high-frequency part, and ...
We propose a novel tracker named ASACTT based on the Siamese network framework, as illustrated in Fig.1. It primarily consists of three parts: Swin-Transformer-based feature extraction, adaptive sparse attention-based feature fusion and prediction head. Firstly, we introduce the feature extraction a...
Convolutional Neural Networks give heavy storage and computation burden to accelerators, whose energy efficiency can be improved by leveraging their sparsity. However, using sparsity in networks will introduce large overhead especially when networks have various sparse situations and multiple quantization. Th...
We present a hierarchical model that learns image decompositions via alternating layers of convolutional sparse coding and max pooling. When trained on natural images, the layers of our model capture image information in a variety of forms: low-level edges, mid-level edge junctions, high-level obj...
paradigm networks. Namely, in the case where two single-paradigm networks perform comparably, the HSTNN has a larger chance to produce a better hybridization solution. In addition to DVS-Gesture, we also test the scalability of the proposed approach in deep convolutional network structures (see ...
轻量级网络-ReXNet:Diminishing Representational Bottleneck on Convolutional Neural Network github 地址:https://arxiv.org/pdf/2007.00992.pdf github:https://github.com/clovaai/rexnet 西西嘛呦 2020/08/26 7270 计算机视觉中常用的注意力机制 pytorchhttpshttp网络安全云联网 注意力机制起初是作为自然语言处理中的...
案例图神经网络gnn100篇集adaptive graph convolutional neural networks.pdf,Adaptive Graph Convolutional Neural Networks Ruoyu Li, Sheng Wang, Feiyun Zhu, Junzhou Huang The University of Texas at Arlington, Arlington, TX 76019, USA Tencent AI Lab, Shenzhen,
introduce another loss function regarding the head count We notice that most representative approaches perform poorly on crowd scenes with few pedestrians. 原来的损失函数不能解决这个问题的原因:because the absolute pedestrian number is usually not very large in sparse crowds compared to that in dense ...