35 citations · 41 across the 7 of their papers we have counts for
7 papers
GeNAS: Neural Architecture Search with Better Generalization
Joonhyun Jeong, Joonsang Yu, Geondo Park +2
Neural Architecture Search (NAS) aims to automatically excavate the optimal network architecture with superior test performance. Recent neural architecture search (NAS) approaches…
The Devil is in the Points: Weakly Semi-Supervised Instance Segmentation via Point-Guided Mask Representation
Beomyoung Kim, Joonhyun Jeong, Dongyoon Han +1
In this paper, we introduce a novel learning scheme named weakly semi-supervised instance segmentation (WSSIS) with point labels for budget-efficient and high-performance instance…
Dataset Condensation via Efficient Synthetic-Data Parameterization
Jang-Hyun Kim, Jinuk Kim, Seong Joon Oh +5
The great success of machine learning with massive amounts of data comes at a price of huge computation costs and storage for training and tuning. Recent studies on dataset condens…
EResFD: Rediscovery of the Effectiveness of Standard Convolution for Lightweight Face Detection
Joonhyun Jeong, Beomyoung Kim, Joonsang Yu +1
This paper analyzes the design choices of face detection architecture that improve efficiency of computation cost and accuracy. Specifically, we re-examine the effectiveness of the…
Observations on K-image Expansion of Image-Mixing Augmentation for Classification
Joonhyun Jeong, Sungmin Cha, Youngjoon Yoo +3
Image-mixing augmentations (e.g., Mixup and CutMix), which typically involve mixing two images, have become the de-facto training techniques for image classification. Despite their…
An Inter-Layer Weight Prediction and Quantization for Deep Neural Networks based on a Smoothly Varying Weight Hypothesis
Kang-Ho Lee, JoonHyun Jeong, Sung-Ho Bae
Due to a resource-constrained environment, network compression has become an important part of deep neural networks research. In this paper, we propose a new compression method, \t…
New pointwise convolution in Deep Neural Networks through Extremely Fast and Non Parametric Transforms
Joonhyun Jeong, Sung-Ho Bae
Some conventional transforms such as Discrete Walsh-Hadamard Transform (DWHT) and Discrete Cosine Transform (DCT) have been widely used as feature extractors in image processing bu…