What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Machine learning
- Programming language
Her scientific interests lie mostly in Smart environment, Home automation, Data mining, Artificial intelligence and Activity recognition.
Her work carried out in the field of Smart environment brings together such families of science as Computational intelligence, Health care, Field, Activities of daily living and Data science.
The various areas that Diane J. Cook examines in her Home automation study include Computer security, Task, Human–computer interaction, Intelligent sensor and Embedded system.
The study incorporates disciplines such as Data stream, Graph and Component in addition to Data mining.
Her study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning, Graph based and Pattern recognition.
Her Activity recognition study integrates concerns from other disciplines, such as Data modeling, Feature, Ubiquitous computing, Sliding window protocol and Focus.
Her most cited work include:
- Review: Ambient intelligence: Technologies, applications, and opportunities (690 citations)
- Sensor-Based Activity Recognition (625 citations)
- How smart are our environments? An updated look at the state of the art (510 citations)
What are the main themes of her work throughout her whole career to date?
Her primary areas of investigation include Artificial intelligence, Home automation, Smart environment, Data mining and Machine learning.
The Artificial intelligence study combines topics in areas such as Graph, Domain, Theoretical computer science and Pattern recognition.
Her Home automation research focuses on subjects like Activity recognition, which are linked to Feature extraction.
The concepts of her Smart environment study are interwoven with issues in Context, Health care, Ubiquitous computing, Testbed and Data science.
Her biological study spans a wide range of topics, including Data compression and Cluster analysis.
Her Machine learning study combines topics in areas such as Intelligent environment and Task.
She most often published in these fields:
- Artificial intelligence (35.98%)
- Home automation (22.18%)
- Smart environment (21.55%)
What were the highlights of her more recent work (between 2015-2021)?
- Home automation (22.18%)
- Artificial intelligence (35.98%)
- Activity recognition (16.74%)
In recent papers she was focusing on the following fields of study:
Diane J. Cook mainly investigates Home automation, Artificial intelligence, Activity recognition, Machine learning and Human–computer interaction.
Diane J. Cook has researched Home automation in several fields, including Smart environment, Change detection, Computer security, Testbed and Process.
Her Smart environment research incorporates elements of Ubiquitous computing and Health care.
Her research integrates issues of Domain adaptation, Set and Pattern recognition in her study of Artificial intelligence.
Diane J. Cook usually deals with Activity recognition and limits it to topics linked to Context and Ecology.
Her Human–computer interaction research is multidisciplinary, incorporating elements of Health informatics and Activities of daily living.
Between 2015 and 2021, her most popular works were:
- A survey of methods for time series change point detection (335 citations)
- A Survey of Unsupervised Deep Domain Adaptation (85 citations)
- Automated Cognitive Health Assessment From Smart Home-Based Behavior Data (80 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Programming language
Her main research concerns Home automation, Artificial intelligence, Activity recognition, Machine learning and Data mining.
Her studies deal with areas such as Smart environment, Computer security, Human–computer interaction, Health informatics and Process as well as Home automation.
Her Smart environment research is multidisciplinary, incorporating perspectives in Testbed and Ubiquitous computing.
Her work deals with themes such as Domain adaptation, Trail Making Test and Data science, which intersect with Artificial intelligence.
Her Activity recognition research includes themes of Context, Feature extraction, Feature selection and Regression analysis.
Her Data mining research integrates issues from Change detection, Behavior change and Time series.
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