Asaf Noy

1.1k total citations · 1 hit paper
6 papers, 409 citations indexed

About

Asaf Noy is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Asaf Noy has authored 6 papers receiving a total of 409 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 1 paper in Computer Networks and Communications. Recurrent topics in Asaf Noy's work include Advanced Image and Video Retrieval Techniques (3 papers), Text and Document Classification Technologies (3 papers) and Advanced Neural Network Applications (2 papers). Asaf Noy is often cited by papers focused on Advanced Image and Video Retrieval Techniques (3 papers), Text and Document Classification Technologies (3 papers) and Advanced Neural Network Applications (2 papers). Asaf Noy collaborates with scholars based in Cayman Islands, Israel and China. Asaf Noy's co-authors include Tal Ridnik, Emanuel Ben-Baruch, Lihi Zelnik‐Manor, Itamar Friedman, Matan Protter, Avi Ben-Cohen, Raja Giryes and Nadav Zamir and has published in prestigious journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

In The Last Decade

Asaf Noy

5 papers receiving 397 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Asymmetric Loss For Multi-Label Classification

2021 323 citations Tal Ridnik, Emanuel Ben-Baruch et al. 2021 IEEE/CVF International Conference on Computer Vision (ICCV) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Asaf Noy Cayman Islands	4	256	205	42	23	21	6	409
Emanuel Ben-Baruch Cayman Islands	3	249 1.0×	199 1.0×	41 1.0×	23 1.0×	21 1.0×	3	400
Tal Ridnik Israel	6	255 1.0×	204 1.0×	41 1.0×	23 1.0×	21 1.0×	8	427
Itamar Friedman Cayman Islands	5	251 1.0×	195 1.0×	41 1.0×	21 0.9×	21 1.0×	6	391
Asim Munir Pakistan	10	186 0.7×	245 1.2×	134 3.2×	10 0.4×	34 1.6×	21	486
Waldir R. De Almeida Brazil	5	140 0.5×	110 0.5×	34 0.8×	44 1.9×	17 0.8×	7	283
Henry Gouk United Kingdom	6	163 0.6×	92 0.4×	31 0.7×	28 1.2×	12 0.6×	14	300
Patrick Kwabena Mensah Ghana	7	119 0.5×	117 0.6×	64 1.5×	21 0.9×	4 0.2×	27	371
Yu Deng China	10	134 0.5×	72 0.4×	76 1.8×	12 0.5×	12 0.6×	35	266
Kaleem Arshid China	8	73 0.3×	102 0.5×	74 1.8×	15 0.7×	36 1.7×	20	358

Countries citing papers authored by Asaf Noy

Since Specialization

Citations

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

Fields of papers citing papers by Asaf Noy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Asaf Noy

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

All Works

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6 of 6 papers shown

1.

Noy, Asaf, et al.. (2024). Diverse Imagenet Models Transfer Better. 1903–1914. 2 indexed citations

2.

Ridnik, Tal, et al.. (2023). ML-Decoder: Scalable and Versatile Classification Head. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 32–41. 50 indexed citations

3.

Ben-Baruch, Emanuel, Tal Ridnik, Itamar Friedman, et al.. (2022). Multi-label Classification with Partial Annotations using Class-aware Selective Loss. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 4754–4762. 27 indexed citations

4.

Noy, Asaf, et al.. (2022). PETA: Photo Albums Event Recognition using Transformers Attention. 2022 26th International Conference on Pattern Recognition (ICPR). 2532–2538.

5.

Ridnik, Tal, Emanuel Ben-Baruch, Asaf Noy, et al.. (2021). Asymmetric Loss For Multi-Label Classification. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 82–91. 323 indexed citations breakdown →

6.

Noy, Asaf, et al.. (2020). ASAP: Architecture Search, Anneal and Prune. International Conference on Artificial Intelligence and Statistics. 493–503. 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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