526互联

interpretable interactions microblogs detection

Center-based 3D Object Detection and Tracking

zotero-key: A37ALEJ3 zt-attachments: - "280" title: Center-based 3D Object Detection and Tracking citekey: yinCenterbased3DObject2021 Center-based 3D ......
Center-based Detection Tracking Center Object

git bash报错fatal: detected dubious ownership in repository at的解决方法

由于新版本的git安全机制，需要核对文件安全性，如果文件夹所以者和当前用户不一致就警告。 方法1，可以把文件的所有者更改为当前用户的 方法2，命令 git config --global --add safe.directory "你的目录或者文件" 意思就是把该目录或者文件白名单安全的 ......
repository ownership detected dubious 方法

Early lameness detection in dairy cattle based on wearable gait analysis using semi-supervised LSTM-Autoencoder

一区top Computers and Electronics in Agriculture 题目：“基于半监督 LSTM-自动编码器可穿戴步态分析的奶牛早期跛行检测” (Zhang 等, 2023, p. 1) (pdf) “Early lameness detection in dairy ca ......
LSTM-Autoencoder semi-supervised Autoencoder supervised detection

Learning Dynamic Query Combinations for Transformer-based Object** Detection and Segmentation论文阅读笔记

Motivation & Intro 基于DETR的目标检测范式（语义分割的Maskformer也与之相似）通常会用到一系列固定的query，这些query是图像中目标对象位置和语义的全局先验。如果能够根据图像的语义信息调整query，就可以捕捉特定场景中物体位置和类别的分布。例如，当高级语义显示图 ......
Transformer-based Combinations Segmentation Transformer Detection

【每周一读】How to Detect Hallucinations in LLMs

准备开一个【每周一读】栏目，分享任何有意思的文章，不定时更新。 原文🔗：https://towardsdatascience.com/real-time-llm-hallucination-detection-9a68bb292698 原文作者：Iulia Brezeanu 1 什么是LLM Ha ......
每周一 Hallucinations Detect LLMs How

1.9 Rotated Multi-Scale Interaction Network for Referring Remote Sensing Image Segmentation 基于语义分割遥感图像的模型

Rotated Multi-Scale Interaction Network for Referring Remote Sensing Image Segmentation 参考遥感图像分割的旋转多尺度交互网络 参考遥感图像分割 (RRSIS)是一个新的挑战，它结合了计算机视觉和自然语言处理，通过 ......
遥感 语义 Segmentation Multi-Scale Interaction

3_5 Interpreters for Languages with Abstraction

3_5 Interpreters for Languages with Abstraction The Calculator language provides a means of combination through nested call expressions. However, ther ......
Interpreters Abstraction Languages with for

Pycharm：添加Python interpreter

1、起因 在编写完一个py文件之后，点击执行，出现以下错误： Error:Python interpreter is not selected. Please setup Python interpreter first. 原因在于，我们还未设置Python解释器 2、解决 ①为pycharm设置一 ......
interpreter Pycharm Python

多组学数据整合 | Multifaceted SOX2-chromatin interaction underpins pluripotency progression in early embryos

最近这篇Science文章不错，Multifaceted SOX2-chromatin interaction underpins pluripotency progression in early embryos - 15 December 2023 需要复刻里面的一些思路、解法和可视化。 复刻【 ......
SOX2-chromatin Multifaceted pluripotency interaction progression

TensorFlow Object Detection API —— 开箱即用的目标检测API

TensorFlow Object Detection API 提供了在 COCO 2017 数据集上预训练的检测模型集合。如果你要识别的对象存在于 COCO2017 数据集，那么你就可以直接使用 TensorFlow Object Detection API 来检测图片或视频。 TensorFlo ......
TensorFlow Detection API 目标 Object

PyQt报错：Cannot load backend 'Qt5Agg' which requires the 'qt5' interactive framework, as 'headless' is currently running

PyQt报错：Cannot load backend 'Qt5Agg' which requires the 'qt5' interactive framework, as 'headless' is currently running 问题描述 在远程链接ubuntu虚拟机进行开发时，报错。 解决 ......
39 interactive framework currently headless

解释器模式 Interpreter

一、定义 给定一个语言，定义他的文法的一种表示 并定义一个解释器，这个解释器使用该表示来解释语言中的句子 二、适用场景 某个特定类型问题发生频率足够高 三、优缺点 1、优点 语法由很多类表示，容易改变及扩展此“语言” 2、缺点 需要预知规则 当语法规则数目太多时，增加了系统复杂度 四、代码实现 ht ......
解释器 Interpreter 模式

论文阅读-Self-supervised and Interpretable Data Cleaning with Sequence Generative Adversarial Networks

1. GARF 简介 代码地址：https://github.com/PJinfeng/Garf-master 基于 SeqGAN 提出了一种自监督、数据驱动的数据清洗框架——GARF。 GARF 的数据清洗分为两个步骤： 规则生成 (Rule generation with SeqGAN)：利用 ......
Self-supervised Interpretable Adversarial Generative supervised

Sw-YoloX An anchor-free detector based transformer for sea surface object detection

Sw-YoloX An anchor-free detector based transformer for sea surface object detection 基于Transformer用于海上目标检测的无锚检测器：Sw-YoloX 1)由于不同海洋状态下的活体和漂浮物体数据稀缺且昂贵，我们 ......
anchor-free transformer detection Sw-YoloX detector

Relation Networks for Object Detection

Relation Networks for Object Detection * Authors: [[Han Hu]], [[Jiayuan Gu]], [[Zheng Zhang]], [[Jifeng Dai]], [[Yichen Wei]] DOI: 10.1109/CVPR.2018.0 ......
Detection Relation Networks Object for

UIU-Net: U-Net in U-Net for Infrared Small Object Detection：Unet中的Unet

UIU-Net: U-Net in U-Net for Infrared Small Object Detection * Authors: [[Xin Wu]], [[Danfeng Hong]], [[Jocelyn Chanussot]] DOI: 10.1109/TIP.2022.32284 ......
Net U-Net Unet Detection Infrared

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 ......
Convolutional Enhancement Detection Adaptive Networks

Predicting Drug-Target Interactions. drug-target interactions prediction

2023 [j22] Junjun Zhang, Minzhu Xie:Graph regularized non-negative matrix factorization with L2,1 norm regularization terms for drug-target interactio ......
Interactions interactions Drug-Target drug-target Predicting

A Guide to Image and Video based Small Object Detection using Deep Learning : Case Study of Maritime Surveillance

A Guide to Image and Video based Small Object Detection using Deep Learning : Case Study of Maritime Surveillance 基于图像和视频的小对象指南使用深度学习进行检测：的案例研究海上监视 1 ......
Surveillance Detection Learning Maritime Object

Object detection in optical remote sensing images: A survey and a new benchmark

Object detection in optical remote sensing images: A survey and a new benchmark 光学遥感图像中的目标检测：调查和新基准 最近人们投入了大量的精力来提出光学遥感图像中物体检测的各种方法。然而，目前对光学遥感图像中目标检测的 ......
detection benchmark optical sensing Object

GGI gene-gene interaction

A novel fuzzy set based multifactor dimensionality reduction method for detecting gene–gene interaction Fuzzy set-based generalized multifactor dimens ......
gene interaction gene-gene GGI

unity 添加插件XR Interaction Toolkit 无法找到的解决办法

若在Unity 中 Package Manager 找不到XR Interaction Toolkit 包，可以点击下图所示的 “+” 号，选择 Add Package from git URL ，输入 com.unity.xr.interaction.toolkit，即可导入 如下图： ......
Interaction 插件 Toolkit 办法 unity

Django 创建项目时找不到数据库sqlite3，提示no changes detected

原因:PyCharm创建Django项目,找不到数据库sqlite3 解决：如果没有默认的db文件，则应在PyCharm终端中执行以下命令： python manage.py makemigrations:提示python manage.py migrate ......
detected sqlite3 changes 数据库 项目

[论文阅读] A unified model for multi-class anomaly detection

A unified model for multi-class anomaly detection 1 Introduction 现有方法[6, 11, 25, 27, 48, 49, 52]建议为不同类别的对象训练单独的模型，就像图1c中的情况一样。然而，这种一类一模型的方案可能会消耗大量内存，尤 ......
multi-class detection unified anomaly 论文

pycharm中三种解释器：virtual Enviroment、conda Enviroment、system interpreter

1、system interpreter不推荐使用 2、Virtual Environment—Python的虚拟环境可以使一个Python程序拥有独立的库library和解释器interpreter，而不用与其他Python程序共享统一个library和interpreter。虚拟环境的好处是避免 ......
Enviroment 解释器 interpreter pycharm virtual

Graph regularized non-negative matrix factorization with prior knowledge consistency constraint for drug-target interactions prediction

Graph regularized non-negative matrix factorization with prior knowledge consistency constraint for drug-target interactions prediction Junjun Zhang 1 ......
factorization non-negative interactions regularized consistency

LPI-IBWA: Predicting lncRNA-protein interactions based on an improved Bi-Random walk algorithm

LPI-IBWA: Predicting lncRNA-protein interactions based on an improved Bi-Random walk algorithm Minzhu Xie 1, Ruijie Xie 2, Hao Wang 3 Affiliations exp ......
lncRNA-protein interactions Predicting Bi-Random algorithm

Graph regularized non-negative matrix factorization with [Formula: see text] norm regularization terms for drug-target interactions prediction

Graph regularized non-negative matrix factorization with [Formula: see text] norm regularization terms for drug-target interactions prediction Junjun ......
regularization factorization non-negative interactions regularized

B4185. LPI-IBWA:Predicting lncRNA-protein Interactions Based on Improved Bi-Random Walk Algorithm

B4185. LPI-IBWA:Predicting lncRNA-protein Interactions Based on Improved Bi-Random Walk Algorithm Minzhu Xie1, Hao Wang1 and Ruijie Xi1 1Hunan Normal ......
lncRNA-protein Interactions Predicting Algorithm Bi-Random

Detecting Unknown Encrypted Malicious Traffic in Real Time via Flow Interaction Graph Analysis

1 前言 1.1 标题 Detecting Unknown Encrypted Malicious Traffic in Real Time via Flow Interaction Graph Analysis 1.2 摘要 为了保护网络的机密性和隐私性，目前互联网上的流量被广泛地加密。然而，流量 ......
Interaction Detecting Encrypted Malicious Analysis
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