Fath U Min Ullah
Fath U Min Ullah publishes mostly in Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence, on topics such as Anomaly Detection Techniques and Applications, Energy Load and Power Forecasting and Video Surveillance and Tracking Methods.
- World rank
- #162,031 of 7,710,434 ranked researchers
- Rank in South Korea
- #898 of 162,609
- Works
- 40
- Citations
- 2.3k
- Citations per work
- 57.3
What does Fath U Min Ullah research?
Fath U Min Ullah's work is mostly in Computer Science (40%), Engineering (28%).
Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.
The fields and subfields, with their numbers
- Physical Sciences2768.2%
- Computer Science1639.8%
- Engineering1128.4%
- Everything else1331.8%
- 1Electrical and Electronic Engineering20% of their works
- 2Computer Vision and Pattern Recognition20% of their works
- 3Artificial Intelligence17% of their works
- 4Safety, Risk, Reliability and Quality5% of their works
- 5Computer Networks and Communications4% of their works
- 6Aerospace Engineering3% of their works
Research topics
Which keywords describe Fath U Min Ullah's research?
The keywords of their largest research topics: Deep Learning, Renewable Energy, Neural Networks, Anomaly Detection, Convolutional Neural Networks, Machine Learning, Electricity Price Forecasting and Load Forecasting.
- Smart Grid
- Intrusion Detection
- Demand Response
- Solar Radiation
- Forecasting
- Visual Tracking
- Unsupervised
- Load Forecasting
- Machine Learning
- Anomaly Detection
- Renewable Energy
- Deep Learning
- Neural Networks
- Convolutional Neural Networks
- Electricity Price Forecasting
- Outlier Detection
- Object Tracking
- Action Recognition
- Pose Estimation
- Computer Vision
- Fire Detection
- Network Security
Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.
All 22 words, with their numbers
- Deep Learning405 topics
- Renewable Energy213 topics
- Neural Networks202 topics
- Anomaly Detection142 topics
- Convolutional Neural Networks132 topics
- Machine Learning112 topics
- Electricity Price Forecasting101 topic
- Load Forecasting101 topic
- Outlier Detection101 topic
- Unsupervised101 topic
- Object Tracking91 topic
- Visual Tracking91 topic
- Action Recognition71 topic
- Forecasting71 topic
- Pose Estimation71 topic
- Solar Radiation71 topic
- Computer Vision41 topic
- Demand Response41 topic
- Fire Detection41 topic
- Intrusion Detection41 topic
- Network Security41 topic
- Smart Grid41 topic
Where does Fath U Min Ullah work?
Fath U Min Ullah's main affiliation in the publication record is Sejong University, South Korea.
How many publications and citations does Fath U Min Ullah have?
OpenAlex counts 40 works and 2,290 citations for Fath U Min Ullah, an h-index of 23, ranking #162,031 of 7,710,434 researchers worldwide on the quality score.
Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.
Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.
Discussion
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