Search Results for author: Byungkon Kang

Found 7 papers, 2 papers with code

Comparative Study: Standalone IEEE 16-bit Floating-Point for Image Classification

no code implementations18 May 2023 Juyoung Yun, Byungkon Kang, Francois Rameau, Zhoulai Fu

Contrary to literature that credits the success of noise-tolerated neural networks to regularization effects, our study-supported by a series of rigorous experiments-provides a quantitative explanation of why standalone IEEE 16-bit floating-point neural networks can perform on par with 32-bit and mixed-precision networks in various image classification tasks.

Image Classification

The Hidden Power of Pure 16-bit Floating-Point Neural Networks

no code implementations30 Jan 2023 Juyoung Yun, Byungkon Kang, Zhoulai Fu

Lowering the precision of neural networks from the prevalent 32-bit precision has long been considered harmful to performance, despite the gain in space and time.

MINSU (Mobile Inventory And Scanning Unit):Computer Vision and AI

no code implementations14 Apr 2022 Jihoon Ryoo, Byungkon Kang, Dongyeob Lee, Seunghyeon Kim, YoungHo Kim

To do so, it goes through a five-step method: object detection, foreground subtraction, K-means clustering, percentage estimation, and counting.

Clustering Management +2

Efficient Deep Neural Network for Photo-realistic Image Super-Resolution

1 code implementation6 Mar 2019 Namhyuk Ahn, Byungkon Kang, Kyung-Ah Sohn

Recent progress in deep learning-based models has improved photo-realistic (or perceptual) single-image super-resolution significantly.

Image Super-Resolution

Fast Determinantal Point Process Sampling with Application to Clustering

no code implementations NeurIPS 2013 Byungkon Kang

In addition, we show that this framework can be extended to sampling from cardinality-constrained DPPs.

Clustering

Cannot find the paper you are looking for? You can Submit a new open access paper.