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  1. Home
  2. /Repositories
  3. /sansan0/TrendRadar
Read original ↗
repoGitHubTrust 82 · PrimaryPublished 20d agoLive · 7d ago

sansan0/TrendRadar

⭐AI-driven public opinion & trend monitor with multi-platform aggregation, RSS, and smart alerts.🎯 告别信息过载,你的 AI 舆情监控助手与热点筛选工具!聚合多平台热点 + RSS 订阅,支持关键词精准筛选。AI 智能筛选新闻 + AI 翻译 + AI 分析简报直推手机,也支持接入 MCP 架构,赋能 AI 自然语言对话分析、情感洞察与趋势预测等。支持 Docker ,数据本地/云端自持。集成微信/飞书/钉钉/Telegram/邮件/ntfy/bark/slack 等渠道智能推送。

Lineage graph

Paper → model → repo connections mined from source citations (Tier-1 exact match).

Why these links exist

Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.

  • PossiblePossibly related (embedding) · 48%The Death of Notifications: Why Software Needs to Learn How to Converse - HackerNoon →
  • PossiblePossibly related (embedding) · 45%Auto Documentation AI - Trend Hunter →
  • FuzzySimilar title/name (fuzzy) · 59%4DR360: State Reasoning for Joint 3D Detection and Occupancy Prediction in 4D Radar-Camera Full-Scene Perception →

    “Fuzzy title match (0.73): “4DR360: State Reasoning for Joint 3D Detection and Occupancy” ≈ “sansan0/TrendRadar””

  • FuzzySimilar title/name (fuzzy) · 59%Learning Structurally Consistent Representations for Multi-View Radar Semantic Segmentation →

    “Fuzzy title match (0.73): “Learning Structurally Consistent Representations for Multi-V” ≈ “sansan0/TrendRadar””

  • FuzzySimilar title/name (fuzzy) · 59%Physics-Based Deep Spatiotemporal Hyperlocal Radar Nowcasting with a Multi-Variable U-Net for High-Resolution Precipitation Forecasting →

    “Fuzzy title match (0.73): “Physics-Based Deep Spatiotemporal Hyperlocal Radar Nowcastin” ≈ “sansan0/TrendRadar””

  • LinkedLinked via github contributor · 85%sansan0 →

    “241 commits”

  • LinkedLinked via github contributor · 85%bing-h →

    “1 commits”

  • LinkedLinked via github contributor · 85%wtychn →

    “1 commits”

Covers

newsThe Death of Notifications: Why Software Needs to Learn How to Converse - HackerNoonnewsAuto Documentation AI - Trend Hunter

Implements

paper4DR360: State Reasoning for Joint 3D Detection and Occupancy Prediction in 4D Radar-Camera Full-Scene PerceptionpaperLearning Structurally Consistent Representations for Multi-View Radar Semantic SegmentationpaperPhysics-Based Deep Spatiotemporal Hyperlocal Radar Nowcasting with a Multi-Variable U-Net for High-Resolution Precipitation Forecasting

contributed_to (incoming)

personsansan0personbing-hpersonwtychn

Related across the graph

paperPhysics-Based Deep Spatiotemporal Hyperlocal Radar Nowcasting with a Multi-Variable U-Net for High-Resolution Precipitation Forecastingpaper4DR360: State Reasoning for Joint 3D Detection and Occupancy Prediction in 4D Radar-Camera Full-Scene PerceptionpaperLearning Structurally Consistent Representations for Multi-View Radar Semantic Segmentationpersonbing-hnewsAuto Documentation AI - Trend Hunterpersonsansan0personwtychnnewsThe Death of Notifications: Why Software Needs to Learn How to Converse - HackerNoon
Knowledge path·PPhysics-Based Deep Spatiotemporal Hyperlocal Radar Nowcasting with a Multi-Variable U-Net for High-Resolution Precipitation Forecasting→P4DR360: State Reasoning for Joint 3D Detection and Occupancy Prediction in 4D Radar-Camera Full-Scene Perception→PLearning Structurally Consistent Representations for Multi-View Radar Semantic Segmentation→Rsansan0/TrendRadar

Topics

aibarkdata-analysisdockerhot-newsllmmailmcpmcp-servernews

Explore

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RIS88GitHub verified
Graph trust82Primary
Graph score60633