crossentropyloss runtimeerror expected network
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network * Authors: [[Wenzhe Shi]], [[Jose Caballer ......
Pyramid Scene Parsing Network
Pyramid Scene Parsing Network * Authors: [[Hengshuang Zhao]], [[Jianping Shi]], [[Xiaojuan Qi]], [[Xiaogang Wang]], [[Jiaya Jia]] DOI: 10.1109/CVPR.20 ......
Asymmetric Non-Local Neural Networks for Semantic Segmentation 非对称注意力
Asymmetric Non-Local Neural Networks for Semantic Segmentation * Authors: [[Zhen Zhu]], [[Mengdu Xu]], [[Song Bai]], [[Tengteng Huang]], [[Xiang Bai]] ......
PIDNet: A Real-time Semantic Segmentation Network Inspired by PID Controllers
PIDNet: A Real-time Semantic Segmentation Network Inspired by PID Controllers * Authors: [[Jiacong Xu]], [[Zixiang Xiong]], [[Shankar P. Bhattacharyya ......
PSANet: Point-wise Spatial Attention Network for Scene Parsing双向注意力
PSANet: Point-wise Spatial Attention Network for Scene Parsing * Authors: [[Hengshuang Zhao]], [[Yi Zhang]], [[Shu Liu]], [[Jianping Shi]], [[Chen Cha ......
Object Tracking Network Based on Deformable Attention Mechanism
Object Tracking Network Based on Deformable Attention Mechanism Local library 初读印象 comment:: (DeTrack)采用基于可变形注意力机制的编码器模块和基于自注意力机制的编码器模块相结合的方式进行特征交互。基于 ......
Adaptive Sparse Convolutional Networks with Global Context Enhancement for Faster Object Detection on Drone Images
Adaptive Sparse Convolutional Networks with Global Context Enhancement for Faster Object Detection on Drone Images * Authors: [[Bowei Du]], [[Yecheng ......
A Deformable Attention Network for High-Resolution Remote Sensing Images Semantic Segmentation可变形注意力
A Deformable Attention Network for High-Resolution Remote Sensing Images Semantic Segmentation * Authors: [[Renxiang Zuo]], [[Guangyun Zhang]], [[Rong ......
SiReN Sign-Aware Recommendation Using Graph Neural Networks论文阅读笔记
Abstract 目前使用GNN的推荐系统主要利用高评分的正向用户-物品交互信息。但是如何利用低评分来表示用户的偏好是一个挑战,因为低评分仍然可以提供有用的信息。所以在本文中提出了基于GNN模型的有符号感知推荐系统SiReN,SiReN有三个关键组件 构造一个符号二部图更精确的表示用户的偏好,分为两 ......
Fully Attentional Network for Semantic Segmentation:FLANet
Fully Attentional Network for Semantic Segmentation * Authors: [[Qi Song]], [[Jie Li]], [[Chenghong Li]], [[Hao Guo]], [[Rui Huang]] 初读印象 comment:: (F ......
PANE-GNN Unifying Positive and Negative Edges in Graph Neural Networks for Recommendation论文阅读笔记
Abstract 目前利用GNN的推荐系统主要关注用户的正面反馈,而忽略了负面反馈提供的见解。于是我们提出了PANG- GNN,该模型将图神经网络的正面和负面边统一在一起。PANG-GNN首先将原始评分图根据正面和负面反馈划分为两个不同的二分图。接下来分别使用两个独立的嵌入,即感兴趣嵌入和无兴趣嵌入 ......
CentOS7配置静态ip后service network restart失败
解决方法: 1、检查配置文件,文件夹下是否存在类似文件(ifcfg-ens33),存在的话,删除掉,保留一个即可(判断方式为配置文件中是否有配置信息) cd /etc/sysconfig/network-scripts/ ls 删除命令: rm 文件名称 重启网络:service network r ......
Machine is not on the network
在调试Android jni 的时候发现一个奇怪的问题 在连接socket的时候老是报错 m_sock = socket(AF_INET, SOCK_STREAM, 0); if(m_sock < 0) { debug(LEVEL_ERROR, "Socket create error %d\r\n ......
使用yarn安装依赖包出现“There appears to be trouble with your network connection. Retrying...”超时的提醒
我们在使用yarn安装依赖包文件的时候,可能会出现“There appears to be trouble with your network connection. Retrying...”超时的提醒,很有可能是因为yarn默认的镜像地址为国外,因此慢(超时)就说得过去了…… 1、问题描述 我们在 ......
0x02 Network Services
Task1、引言 这个房间将探讨常见的网络服务漏洞和错误配置。 Task2、了解SMB 什么是SMB? SMB - 服务器消息块协议 - 是一种客户端-服务器通信协议,用于共享对网络上的文件、打印机、串行端口和其他资源的访问。[source] SMB 协议被称为响应请求协议,这意味着它在客户端和服务 ......
ubuntu18.04.6 编译buildroot的时候提示: Incorrect selection of kernel headers: expected 4.6.x, got 4.16.x
再次进入文件系统配置界面,将内核头文件从4.16.x 改为4.6.x 就可以了。 ......
【报错解决】RuntimeError: An attempt has been made to start a new process...
【报错解决】RuntimeError: An attempt has been made to start a new process… 今天来记录一个Pycharm当中的报错解决: RuntimeError: An attempt has been made to start a new proc ......
yarn按照依赖的时候报 info There appears to be trouble with your network connection. Retrying...
出现这个提示多数情况下是有使用代理软件的结果,我们只需要关闭代理即可1. 更换yarn镜像 yarn config set registry https://registry.npm.taobao.org 2.移除原代理 yarn config delete proxy ......
论文精读:STMGCN利用时空多图卷积网络进行移动边缘计算驱动船舶轨迹预测(STMGCN: Mobile Edge Computing-Empowered Vessel Trajectory Prediction Using Spatio-Temporal Multigraph Convolutional Network)
《STMGCN: Mobile Edge Computing-Empowered Vessel Trajectory Prediction Using Spatio-Temporal Multigraph Convolutional Network》 论文链接:https://doi.org/10. ......
论文精读:基于具有时空感知的稀疏多图卷积混合网络的大数据驱动船舶轨迹预测(Big data driven trajectory prediction based on sparse multi-graph convolutional hybrid network withspatio-temporal awareness)
论文精读:基于具有时空感知的稀疏多图卷积混合网络的大数据驱动船舶轨迹预测 《Big data driven vessel trajectory prediction based on sparse multi-graph convolutional hybrid network with spati ......
Retentive Networks Meet Vision Transformers, 视觉RetNet
alias: Fan2023 tags: RetNet rating: ⭐ share: false ptype: article RMT: Retentive Networks Meet Vision Transformers 初读印象 comment:: (RMT)Retentive Netwo ......
How to Use Docker and NS-3 to Create Realistic Network Simulations
https://insights.sei.cmu.edu/blog/how-to-use-docker-and-ns-3-to-create-realistic-network-simulations/ How to Use Docker and NS-3 to Create Realistic N ......
A novel essential protein identification method based on PPI networks and gene expression data
A novel essential protein identification method based on PPI networks and gene expression data Jiancheng Zhong 1 2, Chao Tang 1, Wei Peng 3, Minzhu Xi ......
A Novel Approach Based on Bipartite Network Recommendation and KATZ Model to Predict Potential Micro-Disease Associations
A Novel Approach Based on Bipartite Network Recommendation and KATZ Model to Predict Potential Micro-Disease Associations Shiru Li 1, Minzhu Xie 1, Xi ......
Predicting gene expression from histone modifications with self-attention based neural networks and transfer learning
Predicting gene expression from histone modifications with self-attention based neural networks and transfer learning Yuchi Chen 1, Minzhu Xie 1, Jie ......
LOEUF (the loss-of-function observed/expected upper bound fraction) 和 pLI (probability of being Loss-of-function Intoleran)
LOEUF (the loss-of-function observed/expected upper bound fraction): LOEUF is a conservative estimate of evolutionary selection against disease-causin ......
celery 5.3.6 报错ValueError: not enough values to unpack (expected 3, got 0)
celery 5.3.6 报错ValueError: not enough values to unpack 启动celery脚本报错 执行 python run_task.py报错,celery服务端和脚本端日志信息如下 # celery -A tasks worker --loglevel=IN ......
Erasing, Transforming, and Noising Defense Network for Occluded Person Re-Identification
三个分支:擦除、转换、噪声 用来生成对抗性表征,模拟遮挡问题 对应信息丢失、位置错位和噪声信息 对抗性防御:思路是GAN网络,以对抗性的方式优化生成器和判别器 ......
java.lang.IllegalStateException: Expected BEGIN_OBJECT but was STRING at line 1 column 2 path $
java.lang.IllegalStateException: Expected BEGIN_OBJECT but was STRING at line 1 column 2 path $ package com.example.core.mydemo.scooterOrderSms; impor ......
go network poller 一
网络基础 协议架构 tcp链接 假如需要开发者去实现一套新的网络协议(例如 redis 的resp), 是基于TCP的, 那tcp这层的协议,是否需要开发者自己去实现? 这层如果自己实现, 其实很复杂, 会涉及很多算法相关. 因此, 出现了 socket 对传输层进行了抽象, 开发者不需要关注传输层 ......