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Dick Ameln

1 paper here

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author position
  • middle author1

Across the 1 of 1 paper where every author was matched, so the position is known.

fields
  • cs.CV1
ORCID 0000-0002-1887-1483
same name
  • Dick Ameln — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedDivide and Conquer: High-Resolution Industrial Anomaly Detection via Memory Efficient Tiled Ensemble

1 citations · 1 across the 1 of their papers we have counts for

collaborators
Showing cs.CVShow all

3 papers · 1 filter

cs.CV2025

From Benchmarks to Reality: Advancing Visual Anomaly Detection by the VAND 3.0 Challenge

Lars Heckler-Kram, Ashwin Vaidya, Jan-Hendrik Neudeck +4

Visual anomaly detection is a strongly application-driven field of research. Consequently, the connection between academia and industry is of paramount importance. In this regard,…

cs.CV2025

Beyond Academic Benchmarks: Critical Analysis and Best Practices for Visual Industrial Anomaly Detection

Aimira Baitieva, Yacine Bouaouni, Alexandre Briot +3

Anomaly detection (AD) is essential for automating visual inspection in manufacturing. This field of computer vision is rapidly evolving, with increasing attention towards real-wor…

cs.CV2024★ 1 cited

Divide and Conquer: High-Resolution Industrial Anomaly Detection via Memory Efficient Tiled Ensemble

Blaž Rolih, Dick Ameln, Ashwin Vaidya +1

Industrial anomaly detection is an important task within computer vision with a wide range of practical use cases. The small size of anomalous regions in many real-world datasets n…

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