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road condition analysis

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Amap Tech
Amap Tech
Feb 1, 2021 · Artificial Intelligence

AMAP-TECH Algorithm Competition: Dynamic Road Condition Analysis Using In-Vehicle Video

The AMAP‑TECH competition challenged participants to infer real‑time road conditions from in‑vehicle video, prompting the authors to combine lane‑wise vehicle detection with LightGBM and later an end‑to‑end DenseNet‑GRU model, augment data, ensemble five networks, and achieve a 0.7237 F1 score while outlining future deployment and research directions.

Deep Learningcomputer visionfeature engineering
0 likes · 15 min read
AMAP-TECH Algorithm Competition: Dynamic Road Condition Analysis Using In-Vehicle Video
Amap Tech
Amap Tech
Jan 22, 2021 · Artificial Intelligence

Dynamic Road Condition Analysis Using EfficientNet and ConvLSTM: Solution to the AMAP‑TECH Algorithm Competition

The winning solution for the AMAP‑TECH competition combines EfficientNet spatial features with ConvLSTM temporal modeling, adds a mask‑prediction branch for closed‑road obstacles, and mitigates severe class imbalance through a two‑stage decoupled training pipeline, achieving first place on leaderboard A and top‑5 on leaderboard B without ensembling.

AI competitionConvLSTMEfficientNet
0 likes · 7 min read
Dynamic Road Condition Analysis Using EfficientNet and ConvLSTM: Solution to the AMAP‑TECH Algorithm Competition