Manoj Acharya

680 total citations · 1 hit paper
6 papers, 115 citations indexed

About

Manoj Acharya is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Civil and Structural Engineering. According to data from OpenAlex, Manoj Acharya has authored 6 papers receiving a total of 115 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 2 papers in Civil and Structural Engineering. Recurrent topics in Manoj Acharya's work include Domain Adaptation and Few-Shot Learning (3 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Multimodal Machine Learning Applications (2 papers). Manoj Acharya is often cited by papers focused on Domain Adaptation and Few-Shot Learning (3 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Multimodal Machine Learning Applications (2 papers). Manoj Acharya collaborates with scholars based in United States and Nepal. Manoj Acharya's co-authors include Kyungki Kim, Christopher Kanan, Kushal Kafle, Dipak Kumar Gupta, Ajay Divakaran, Susmit Jha and Anirban Roy and has published in prestigious journals such as Buildings, Proceedings of the AAAI Conference on Artificial Intelligence and Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence.

In The Last Decade

Manoj Acharya

6 papers receiving 110 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.

Opportunities and Challenges of Generative AI in Construction Industry: Focusing on Adoption of Text-Based Models

2024 61 citations Kyungki Kim, Manoj Acharya et al. Buildings profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Manoj Acharya United States	5	38	35	29	21	16	6	115
Giulio Petrucci Italy	7	136 3.6×	15 0.4×	9 0.3×	6 0.3×	6 0.4×	9	246
Chairma Lakshmi K R India	8	17 0.4×	7 0.2×	3 0.1×	7 0.3×	3 0.2×	24	124
Noel Varela Colombia	7	15 0.4×	21 0.6×	11 0.4×	25 1.2×	1 0.1×	19	124
Harsh Agrawal India	7	45 1.2×	22 0.6×	5 0.2×	4 0.2×	9 0.6×	17	125
Yong Liang China	6	36 0.9×	38 1.1×	14 0.5×	4 0.2×		24	99
Sheng Zhu China	6	17 0.4×	11 0.3×	4 0.1×	7 0.3×	4 0.3×	11	87
Dawid Wiśniewski Poland	10	49 1.3×	3 0.1×	61 2.1×	199 9.5×	12 0.8×	22	274
Peixin Zhao China	10	49 1.3×	7 0.2×	3 0.1×	26 1.2×	5 0.3×	57	381
Ashish Khetan United States	5	24 0.6×	10 0.3×	5 0.2×	7 0.3×		10	56

Countries citing papers authored by Manoj Acharya

Since Specialization

Citations

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

Fields of papers citing papers by Manoj Acharya

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Manoj Acharya

This figure shows the co-authorship network connecting the top 25 collaborators of Manoj Acharya. A scholar is included among the top collaborators of Manoj Acharya 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 Manoj Acharya. Manoj Acharya 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.

Kim, Kyungki, et al.. (2024). Opportunities and Challenges of Generative AI in Construction Industry: Focusing on Adoption of Text-Based Models. Buildings. 14(1). 220–220. 61 indexed citations breakdown →

2.

Acharya, Manoj, et al.. (2022). Detecting Out-Of-Context Objects Using Graph Contextual Reasoning Network. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 629–635. 7 indexed citations

3.

Acharya, Manoj, Kushal Kafle, & Christopher Kanan. (2019). TallyQA: Answering Complex Counting Questions. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 8076–8084. 24 indexed citations

4.

Acharya, Manoj, et al.. (2019). . 1955–1961. 4 indexed citations

5.

Acharya, Manoj, et al.. (2016). Computer Vision Based Hand Gesture Recognition For Speech Disabled Persons. Journal of the Institute of Engineering. 11(1). 30–35. 1 indexed citations

6.

Acharya, Manoj, et al.. (2013). Green Inhibitors for Prevention of Metal and Alloys Corrosion: An Overview. VNU Journal of Science: Natural Sciences and Technology (Vietnam National University). 3(6). 16–24. 18 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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