Andre Guntoro

782 total citations
40 papers, 405 citations indexed

About

Andre Guntoro is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Andre Guntoro has authored 40 papers receiving a total of 405 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Electrical and Electronic Engineering, 18 papers in Computer Vision and Pattern Recognition and 15 papers in Artificial Intelligence. Recurrent topics in Andre Guntoro's work include Advanced Neural Network Applications (17 papers), Advanced Memory and Neural Computing (15 papers) and Ferroelectric and Negative Capacitance Devices (12 papers). Andre Guntoro is often cited by papers focused on Advanced Neural Network Applications (17 papers), Advanced Memory and Neural Computing (15 papers) and Ferroelectric and Negative Capacitance Devices (12 papers). Andre Guntoro collaborates with scholars based in Germany, Netherlands and Belgium. Andre Guntoro's co-authors include Gerd Ascheid, Sebastian Vogel, Akash Kumar, Norbert Wehn, Thomas Kämpfe, Franz Müller, Walter Stechele, Maximilian Lederer, Tarek Ali and Manfred Glesner and has published in prestigious journals such as SHILAP Revista de lepidopterología, Future Generation Computer Systems and IEEE Micro.

In The Last Decade

Andre Guntoro

37 papers receiving 395 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Andre Guntoro Germany 10 278 133 127 62 31 40 405
Yun Long United States 10 329 1.2× 108 0.8× 111 0.9× 41 0.7× 19 0.6× 27 407
Guohao Dai China 10 199 0.7× 160 1.2× 157 1.2× 113 1.8× 16 0.5× 46 432
Jon J. Pimentel United States 6 158 0.6× 136 1.0× 85 0.7× 80 1.3× 20 0.6× 8 303
Yuxiang Fu China 11 243 0.9× 45 0.3× 92 0.7× 55 0.9× 45 1.5× 69 377
En-Yu Yang United States 8 494 1.8× 131 1.0× 151 1.2× 91 1.5× 18 0.6× 15 620
Philipp Gysel United States 4 197 0.7× 251 1.9× 123 1.0× 47 0.8× 13 0.4× 5 347
Hyunjoon Kim Singapore 15 407 1.5× 134 1.0× 221 1.7× 115 1.9× 37 1.2× 23 595
Jeng-Hau Lin United States 8 290 1.0× 241 1.8× 149 1.2× 83 1.3× 9 0.3× 17 479
Nicholas J. Fraser Australia 7 198 0.7× 187 1.4× 138 1.1× 72 1.2× 22 0.7× 18 374
Joonho Song South Korea 7 179 0.6× 105 0.8× 65 0.5× 106 1.7× 16 0.5× 16 311

Countries citing papers authored by Andre Guntoro

Since Specialization
Citations

This map shows the geographic impact of Andre Guntoro'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 Andre Guntoro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andre Guntoro more than expected).

Fields of papers citing papers by Andre Guntoro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andre Guntoro. 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 Andre Guntoro. The network helps show where Andre Guntoro may publish in the future.

Co-authorship network of co-authors of Andre Guntoro

This figure shows the co-authorship network connecting the top 25 collaborators of Andre Guntoro. A scholar is included among the top collaborators of Andre Guntoro 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 Andre Guntoro. Andre Guntoro is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Cramer, Benjamin, et al.. (2024). Synthetic data generation techniques for training deep acoustic siren identification networks. SHILAP Revista de lepidopterología. 4. 3 indexed citations
2.
Cramer, Benjamin, et al.. (2024). Auditory Anomaly Detection using Recurrent Spiking Neural Networks. 278–281. 1 indexed citations
3.
4.
Bondi, Luca, et al.. (2024). Can Synthetic Data Boost the Training of Deep Acoustic Vehicle Counting Networks?. Lirias (KU Leuven). 631–635. 3 indexed citations
5.
Weis, Christian, et al.. (2022). A Weighted Current Summation Based Mixed Signal DRAM-PIM Architecture for Deep Neural Network Inference. IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 12(2). 367–380. 5 indexed citations
6.
Laleni, Nellie, et al.. (2022). FELIX: A Ferroelectric FET Based Low Power Mixed-Signal In-Memory Architecture for DNN Acceleration. ACM Transactions on Embedded Computing Systems. 21(6). 1–25. 20 indexed citations
7.
Guntoro, Andre, et al.. (2022). Increasing Throughput of In-Memory DNN Accelerators by Flexible Layerwise DNN Approximation. IEEE Micro. 42(6). 17–24. 3 indexed citations
8.
Guntoro, Andre, et al.. (2022). Fault-tolerant Radar Signal Processing using Selective Observation Windows and Peak Detection. 2022 30th European Signal Processing Conference (EUSIPCO). 1876–1880.
9.
Guntoro, Andre, et al.. (2021). Adaptable Approximation Based on Bit Decomposition for Deep Neural Network Accelerators. 1–4. 3 indexed citations
10.
Olivo, Ricardo, et al.. (2020). A Ferroelectric FET Based In-memory Architecture for Multi-Precision Neural Networks. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 96–101. 5 indexed citations
11.
Guntoro, Andre, et al.. (2020). Full Approximation of Deep Neural Networks through Efficient Optimization. 1–5. 3 indexed citations
12.
Guntoro, Andre, et al.. (2020). Next Generation Arithmetic for Edge Computing. HAL (Le Centre pour la Communication Scientifique Directe). 1357–1365. 15 indexed citations
13.
Müller, Franz, Tarek Ali, Maximilian Lederer, et al.. (2020). Ultra-Low Power Flexible Precision FeFET Based Analog In-Memory Computing. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 29.2.1–29.2.4. 79 indexed citations
14.
Vogel, Sebastian, et al.. (2019). Self-Supervised Quantization of Pre-Trained Neural Networks for Multiplierless Acceleration. 1094–1099. 21 indexed citations
15.
Vogel, Sebastian, et al.. (2019). Bit-Shift-Based Accelerator for CNNs with Selectable Accuracy and Throughput. 663–667. 1 indexed citations
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17.
18.
Guntoro, Andre & Manfred Glesner. (2008). Low-latency VLSI architecture of a 3-input floating-point adder. 180–183. 1 indexed citations
19.
Guntoro, Andre & Manfred Glesner. (2008). High-performance fpga-based floating-point adder with three inputs. 627–630. 4 indexed citations
20.
Guntoro, Andre, et al.. (2007). Low-Complexity Adaptive Encoding Schemes Based on Partial Bus-Invert for Power Reduction in Buses Exhibiting Capacitive Coupling.. 7–14.

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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