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Amap Tech
Amap Tech
Mar 12, 2021 · Fundamentals

MTA Problem in High‑Precision LiDAR Data and Its Correction Algorithms

The article describes how high‑frequency LiDAR scanners on precision mapping vehicles suffer from Multi‑Time‑Around (MTA) errors—mis‑assigning distant returns to near ranges—and explains both internal laser strategies (continuity assumption and variable‑period emission) and a four‑step neighborhood‑weighting algorithm that reliably corrects these artifacts, restoring accurate point‑clouds for automated map generation.

AlgorithmData ProcessingLiDAR
0 likes · 12 min read
MTA Problem in High‑Precision LiDAR Data and Its Correction Algorithms
JD Tech
JD Tech
Jan 28, 2019 · Big Data

Technical Overview of JD Marketing 360: 4A Consumer Asset Model, 4E Marketing Framework, and Big Data Architecture

The article presents a comprehensive technical analysis of JD's Marketing 360 project, detailing the three industry pain points, the 4A consumer‑asset model, the 4E marketing methodology, and the underlying big‑data, AI‑driven architecture that enables real‑time analytics, multi‑modal model training, and performance optimizations.

Artificial IntelligenceBig DataCustomer Asset Model
0 likes · 14 min read
Technical Overview of JD Marketing 360: 4A Consumer Asset Model, 4E Marketing Framework, and Big Data Architecture