What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Computer vision
- Electrical engineering
Aini Hussain spends much of her time researching Artificial intelligence, Artificial neural network, Algorithm, Pattern recognition and Battery.
Her work deals with themes such as Digital signal, Machine learning, Computer vision and Signal processing, which intersect with Artificial intelligence.
Her Artificial neural network study integrates concerns from other disciplines, such as Data mining, Process, Robustness and Water resources.
Her Pattern recognition research incorporates elements of Image processing, Modal and Biometrics.
Her research integrates issues of Electric vehicle and Energy management system in her study of Battery.
Her State of charge research incorporates themes from Extreme learning machine, Management system and Electrical engineering.
Her most cited work include:
- A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations (517 citations)
- Energy harvesting for the implantable biomedical devices: issues and challenges (163 citations)
- State-of-the-Art and Energy Management System of Lithium-Ion Batteries in Electric Vehicle Applications: Issues and Recommendations (154 citations)
What are the main themes of her work throughout her whole career to date?
Her main research concerns Artificial intelligence, Computer vision, Pattern recognition, Feature extraction and Artificial neural network.
Her research on Artificial intelligence frequently connects to adjacent areas such as Machine learning.
Her Speech recognition research extends to Pattern recognition, which is thematically connected.
Her Feature extraction study frequently links to other fields, such as Contextual image classification.
Her research in Artificial neural network intersects with topics in State of charge, Control theory and Electric power system.
The study incorporates disciplines such as Time domain and Maximum power transfer theorem in addition to Electric power system.
She most often published in these fields:
- Artificial intelligence (41.25%)
- Computer vision (23.34%)
- Pattern recognition (17.30%)
What were the highlights of her more recent work (between 2017-2021)?
- Artificial intelligence (41.25%)
- Pattern recognition (17.30%)
- State of charge (2.62%)
In recent papers she was focusing on the following fields of study:
Aini Hussain mostly deals with Artificial intelligence, Pattern recognition, State of charge, Electric vehicle and Artificial neural network.
Her Artificial intelligence research is multidisciplinary, incorporating perspectives in Keratoconus and Computer vision.
Her State of charge research includes elements of Algorithm, Recurrent neural network and Robustness.
Her Electric vehicle research integrates issues from Battery, Automotive engineering and Key.
Particularly relevant to Lithium-ion battery is her body of work in Battery.
Her research investigates the link between Artificial neural network and topics such as Voltage that cross with problems in Control engineering.
Between 2017 and 2021, her most popular works were:
- State-of-the-Art and Energy Management System of Lithium-Ion Batteries in Electric Vehicle Applications: Issues and Recommendations (154 citations)
- A review of state of health and remaining useful life estimation methods for lithium-ion battery in electric vehicles: Challenges and recommendations (135 citations)
- Review of Energy Storage System Technologies in Microgrid Applications: Issues and Challenges (130 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Electrical engineering
Aini Hussain focuses on State of charge, Electric vehicle, Battery, Robustness and Artificial neural network.
The State of charge study combines topics in areas such as Algorithm and Key.
Her studies in Electric vehicle integrate themes in fields like Fault and Lithium-ion battery.
Her Battery research is multidisciplinary, relying on both Automotive engineering, Energy management system, Power density and Condition monitoring.
Her work in Artificial neural network addresses subjects such as Voltage, which are connected to disciplines such as Transmission system.
Noise is often connected to Artificial intelligence in her work.
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