Sangjun Lee, an integrated MS/PhD student in Electrical Engineering (advisor: Professor Sang Woo Kim), received a Best Poster Award at the 15th IEEE International Conference on Machine Learning and Applications (ICMLA 2016) for “Recognition of slab identification numbers using a deep convolutional neural network.”

The paper addresses image processing and pattern recognition for slab product numbers in steelmaking. It proposes an effective deep convolutional neural network method for accurately recognizing numbers distorted or faded by high temperatures against complex backgrounds.

The conference featured 185 papers: 107 oral presentations and 78 posters. Three oral papers received Best Paper Awards, and three posters received Best Poster Awards.

One of the leading conferences in AI applications, ICMLA had an acceptance rate of 24.69% this year, with 31.98% for the poster session. Held in Anaheim, California, USA, it brought together academics, researchers, and industry participants interested in machine learning theory and applications to present their findings.