3 citations · 3 across the 2 of their papers we have counts for
4 papers
Automatic Detection of Injection and Press Mold Parts on 2D Drawing Using Deep Neural Network
Junseok Lee, Jongwon Kim, Jumi Park +3
This paper proposes a method to automatically detect the key feature parts in a CAD of commercial TV and monitor using a deep neural network. We developed a deep learning pipeline…
Object Detection for Understanding Assembly Instruction Using Context-aware Data Augmentation and Cascade Mask R-CNN
Joosoon Lee, Seongju Lee, Seunghyeok Back +2
Understanding assembly instruction has the potential to enhance the robot s task planning ability and enables advanced robotic applications. To recognize the key components from th…
Segmenting Unseen Industrial Components in a Heavy Clutter Using RGB-D Fusion and Synthetic Data
Seunghyeok Back, Jongwon Kim, Raeyoung Kang +2
Segmentation of unseen industrial parts is essential for autonomous industrial systems. However, industrial components are texture-less, reflective, and often found in cluttered an…
Intra- and Inter-epoch Temporal Context Network (IITNet) Using Sub-epoch Features for Automatic Sleep Scoring on Raw Single-channel EEG
Hogeon Seo, Seunghyeok Back, Seongju Lee +3
A deep learning model, named IITNet, is proposed to learn intra- and inter-epoch temporal contexts from raw single-channel EEG for automatic sleep scoring. To classify the sleep st…