What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Statistics
His primary scientific interests are in Artificial intelligence, Pattern recognition, Fuzzy logic, Computer vision and Fuzzy classification.
His Artificial intelligence study is mostly concerned with Thresholding, Segmentation, Histogram, Pixel and Image segmentation.
His work on Principal component analysis and Mixture model as part of general Pattern recognition research is often related to Statistical analysis, thus linking different fields of science.
His Principal component analysis study combines topics from a wide range of disciplines, such as Speech recognition and Right bundle branch block.
His research in Fuzzy logic intersects with topics in Data mining and Image retrieval.
His Fuzzy classification research is multidisciplinary, relying on both Balanced histogram thresholding, Fuzzy set operations and Fuzzy clustering.
His most cited work include:
- Image Processing - Principles and Applications (558 citations)
- Application of principal component analysis to ECG signals for automated diagnosis of cardiac health (175 citations)
- Cardiac decision making using higher order spectra (120 citations)
What are the main themes of his work throughout his whole career to date?
Artificial intelligence, Pattern recognition, Computer vision, Pathology and Segmentation are his primary areas of study.
His study in Fuzzy logic, Image processing, Image segmentation, Feature extraction and Pixel falls within the category of Artificial intelligence.
His studies in Pattern recognition integrate themes in fields like Speech recognition, Fuzzy classification and Thresholding.
His Fuzzy classification research is multidisciplinary, incorporating elements of Fuzzy number, Defuzzification, Fuzzy set operations and Membership function.
His study connects Fuzzy set and Computer vision.
Ajoy Kumar Ray has researched Support vector machine in several fields, including Artificial neural network and Wavelet.
He most often published in these fields:
- Artificial intelligence (61.27%)
- Pattern recognition (37.75%)
- Computer vision (26.96%)
What were the highlights of his more recent work (between 2013-2021)?
- Artificial intelligence (61.27%)
- Pattern recognition (37.75%)
- Computer vision (26.96%)
In recent papers he was focusing on the following fields of study:
His main research concerns Artificial intelligence, Pattern recognition, Computer vision, Fuzzy logic and Compressed sensing.
His study in Segmentation, Deep learning, Wavelet, Thresholding and Artificial neural network falls under the purview of Artificial intelligence.
Ajoy Kumar Ray works mostly in the field of Thresholding, limiting it down to topics relating to Gastroenterology and, in certain cases, Pathology.
Specifically, his work in Pattern recognition is concerned with the study of Mixture model.
In general Computer vision, his work in Image processing, Automatic image annotation and Visual Word is often linked to Scheme linking many areas of study.
His Fuzzy logic research is multidisciplinary, relying on both Voronoi diagram, Content-based image retrieval, Piecewise linear function and Feature extraction.
Between 2013 and 2021, his most popular works were:
- High-Magnification Multi-views Based Classification of Breast Fine Needle Aspiration Cytology Cell Samples Using Fusion of Decisions from Deep Convolutional Networks (18 citations)
- Multiple entropies performance measure for detection and localization of multi-channel epileptic EEG (15 citations)
- Wavelet-based Machine Learning Techniques for ECG Signal Analysis (15 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Pathology, Oral submucous fibrosis and Immunohistochemistry.
His work carried out in the field of Artificial intelligence brings together such families of science as Breast cancer and Computer vision.
His work on Artifact, Wavelet transform and Image correction is typically connected to Band-stop filter as part of general Computer vision study, connecting several disciplines of science.
His Pattern recognition research focuses on Entropy and how it connects with Ground truth.
His study in the field of Dysplasia is also linked to topics like Molecular pathology and Endoglin.
As part of the same scientific family, he usually focuses on Thresholding, concentrating on Divergence and intersecting with Fuzzy classification, Fuzzy logic and Membership function.
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