Joonho Song

800 total citations
16 papers, 311 citations indexed

About

Joonho Song is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Electrical and Electronic Engineering. According to data from OpenAlex, Joonho Song has authored 16 papers receiving a total of 311 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 7 papers in Signal Processing and 6 papers in Electrical and Electronic Engineering. Recurrent topics in Joonho Song's work include Video Coding and Compression Technologies (7 papers), Ferroelectric and Negative Capacitance Devices (4 papers) and Advanced Memory and Neural Computing (4 papers). Joonho Song is often cited by papers focused on Video Coding and Compression Technologies (7 papers), Ferroelectric and Negative Capacitance Devices (4 papers) and Advanced Memory and Neural Computing (4 papers). Joonho Song collaborates with scholars based in South Korea, United States and India. Joonho Song's co-authors include Junwoo Jang, Jun‐Seok Park, Inyup Kang, Sehwan Lee, Jae-Gon Lee, Jeong‐Hyeon Cho, Kyomin Sohn, Nam Sung Kim, Yeongon Cho and Sukhan Lee and has published in prestigious journals such as IEEE Micro, IEEE Transactions on Dependable and Secure Computing and EURASIP Journal on Image and Video Processing.

In The Last Decade

Joonho Song

13 papers receiving 298 citations

Peers

Joonho Song

EEE

HA

CVPR

CNC

AI

Siying Feng United States

Aporva Amarnath United States

Vikram Jain Belgium

Subhankar Pal United States

Sheng-Chun Kao United States

Shang Li United States

Zhaoshi Li China

Licheng Guo United States

Hanchen Jin United States

Pengcheng Yao China

Siying Feng United States

Joonho Song

128 ×0.7

EEE

226 ×2.1

HA

122 ×1.2

CVPR

156 ×1.8

CNC

90 ×1.4

AI

Citations per year, relative to Joonho Song Joonho Song (= 1×) peers Siying Feng

Countries citing papers authored by Joonho Song

Since Specialization

Citations

This map shows the geographic impact of Joonho Song's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Joonho Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joonho Song more than expected).

Fields of papers citing papers by Joonho Song

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joonho Song. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Joonho Song. The network helps show where Joonho Song may publish in the future.

Co-authorship network of co-authors of Joonho Song

This figure shows the co-authorship network connecting the top 25 collaborators of Joonho Song. A scholar is included among the top collaborators of Joonho Song based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Joonho Song. Joonho Song is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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16 of 16 papers shown

1.

Xiong, Wenjie, Liu Ke, Yeongon Cho, et al.. (2025). Accelerating Confidential Recommendation Model Inference With Near-Memory Processing. IEEE Transactions on Dependable and Secure Computing. 22(4). 3580–3586.

2.

Gribov, Y., et al.. (2023). Accelerating Deep Neural Networks on Mobile Multicore NPUs. 236–248. 3 indexed citations

3.

Kang, Shin-haeng, Sukhan Lee, Hyeonsu Kim, et al.. (2022). Aquabolt-XL HBM2-PIM, LPDDR5-PIM With In-Memory Processing, and AXDIMM With Acceleration Buffer. IEEE Micro. 42(3). 20–30. 27 indexed citations

4.

Ke, Liu, Xuan Zhang, Jong-Geon Lee, et al.. (2021). Near-Memory Processing in Action: Accelerating Personalized Recommendation With AxDIMM. IEEE Micro. 42(1). 116–127. 79 indexed citations

5.

Park, Jun‐Seok, Junwoo Jang, Heonsoo Lee, et al.. (2021). 9.5 A 6K-MAC Feature-Map-Sparsity-Aware Neural Processing Unit in 5nm Flagship Mobile SoC. 152–154. 44 indexed citations

6.

Kang, Shin-haeng, Sukhan Lee, Hyeonsu Kim, et al.. (2021). Aquabolt-XL: Samsung HBM2-PIM with in-memory processing for ML accelerators and beyond. 1–26. 33 indexed citations

7.

Lee, Dong‐Hyun, et al.. (2021). A Novel Sensitivity Metric For Mixed-Precision Quantization With Synthetic Data Generation. 1294–1298. 1 indexed citations

8.

Mitra, Arnab, et al.. (2021). Autotuning LSTM for Accelerated Execution on Edge. 48. 1–5. 1 indexed citations

9.

Park, Jun‐Seok, Junwoo Jang, Sehwan Lee, et al.. (2019). 7.1 An 11.5TOPS/W 1024-MAC Butterfly Structure Dual-Core Sparsity-Aware Neural Processing Unit in 8nm Flagship Mobile SoC. 130–132. 100 indexed citations

10.

Song, Joonho, et al.. (2015). DSP based programmable FHD HEVC decoder. Design, Automation, and Test in Europe. 972–973.

11.

Sim, Donggyu, et al.. (2013). Fast CAVLD of H.264/AVC on bitstream decoding processor. EURASIP Journal on Image and Video Processing. 2013(1). 1 indexed citations

12.

Ryu, Eun‐Kyung, et al.. (2012). Parallel Method for HEVC Deblocking Filter based on Coding Unit Depth Information. Journal of Broadcast Engineering. 17(5). 742–755.

13.

Ryu, Eun‐Kyung, et al.. (2012). Complexity-based Sample Adaptive Offset Parallelism. Journal of Broadcast Engineering. 17(3). 503–518. 2 indexed citations

14.

Song, Joonho, et al.. (2011). H.264/AVC UHD decoder implementation on multi-cluster platform using hybrid parallelization method. 2009. 381–384. 5 indexed citations

15.

Kim, Min‐Soo, et al.. (2010). H.264 decoder on embedded dual core with dynamically load-balanced functional paritioning. 3749–3752. 8 indexed citations

16.

Song, Joonho, et al.. (2010). High-performance memory interface architecture for high-definition video coding application. 3745–3748. 7 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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