Waseem Ullah

38 papers receiving 1.6k citations

Waseem Ullah's Hit Papers

A modified YOLOv5 architecture for efficient fire detection in smart cities 2023 · 101 citations
1010+2+4Years since publication100200300400

Peers

Waseem Ullah
Comparison fields: 5 of 104
  • Computer Vision and Pattern Recognition 589
  • Artificial Intelligence 756
  • Safety, Risk, Reliability and Quality 194
  • Computer Networks and Communications 330
  • Building and Construction 173
Replace Fath U Min Ullah with:
Fath U Min Ullah South Korea
Zulfiqar Ahmad Khan South Korea
Ebrahim Damangir Iran
Mohana India
Liangzhi Li Japan
Fahd N. Al‐Wesabi Saudi Arabia
Mahdi Azizi Iran
李昭 Li Zhao China
Hao Yin China
Haigen Min China
Waseem Ullah relative to Fath U Min Ullah South Korea Fath U Min Ullah's profile →
Citations per field
00.5×1.5×2.1×
Fath U Min Ullah · 1×
Citations per year

Countries citing papers authored by Waseem Ullah

Since Specialization
Citations

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

Fields of papers citing papers by Waseem Ullah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Waseem Ullah, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Waseem Ullah Line = papers co-authored together Waseem Ullah links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A Novel CNN-GRU-Based Hybrid Approach for Short-Term Residential Load Forecasting
Hit paper breakdown →
2020411
2 2020216
3 2021124
4 2021119
5
A modified YOLOv5 architecture for efficient fire detection in smart cities
Hit paper breakdown →
2023101
6 202396
7 202073
8 202271
9 202269
10 202348
11 202347
12 202440
13 202332
14 202422
15 202519
16 202418
17 202317
18 202216
19 202514
20 202113

About Waseem Ullah

Waseem Ullah is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Safety, Risk, Reliability and Quality, Artificial Intelligence and Building and Construction, having authored 40 papers that have together received 1.7k indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (14 papers), Video Surveillance and Tracking Methods (14 papers), Network Security and Intrusion Detection (11 papers), Fire Detection and Safety Systems (7 papers), Energy Load and Power Forecasting (4 papers), Human Pose and Action Recognition (4 papers), Machine Learning in Bioinformatics (3 papers) and Data-Driven Disease Surveillance (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (589 citations), Artificial Intelligence (756 citations), Safety, Risk, Reliability and Quality (194 citations), Computer Networks and Communications (330 citations) and Building and Construction (173 citations). Waseem Ullah has collaborated with scholars based in South Korea, United Arab Emirates and Pakistan. Frequent co-authors include Sung Wook Baik, Zulfiqar Ahmad Khan, Tanveer Hussain, Amin Ullah, Muhammad Husain As Sajjad, Mi Young Lee, Fath U Min Ullah, Khan Muhammad, Hikmat Yar and Ijaz Ul Haq. Their work appears in journals such as Expert Systems with Applications, Multimedia Tools and Applications, Image and Vision Computing, IEEE Internet of Things Journal and Engineering Applications of Artificial Intelligence.

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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