The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Pattern recognition, Image segmentation and Image retrieval. As a part of the same scientific family, he mostly works in the field of Artificial intelligence, focusing on Machine learning and, on occasion, Fuzzy set. His study on Pixel, Standard illuminant, Edge detection and Thresholding is often connected to Pigmented skin as part of broader study in Computer vision.
Gerald Schaefer has researched Pattern recognition in several fields, including Local binary patterns, Skin cancer and Mean-shift. The various areas that he examines in his Image retrieval study include Visualization and Database. His Database study incorporates themes from Quantization, Quantization, Color image, Uncompressed video and Ground truth.
His main research concerns Artificial intelligence, Computer vision, Pattern recognition, Image retrieval and Feature extraction. Artificial intelligence and Machine learning are commonly linked in his work. His Machine learning research incorporates themes from Fuzzy classification and Fuzzy logic.
In his study, Palette is inextricably linked to Cluster analysis, which falls within the broad field of Pattern recognition. His work carried out in the field of Image retrieval brings together such families of science as JPEG and Information retrieval. His Image segmentation research is multidisciplinary, incorporating elements of Edge detection, Thresholding and Medical imaging.
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Computer vision, Image and Artificial neural network. His Artificial intelligence study frequently links to other fields, such as Machine learning. His Pattern recognition research integrates issues from Pixel, Histogram, Local binary patterns and Image quality.
His Computer vision research focuses on Image retrieval and JPEG 2000. Gerald Schaefer combines subjects such as Visualization and Information retrieval with his study of Image. His studies in Artificial neural network integrate themes in fields like Fuzzy logic and Pattern recognition.
His main research concerns Artificial intelligence, Pattern recognition, Metaheuristic, Classifier and Image segmentation. His Machine learning research extends to Artificial intelligence, which is thematically connected. His studies deal with areas such as Feature and Medical imaging as well as Pattern recognition.
His Metaheuristic study also includes
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UCID: an uncompressed color image database
Gerald Schaefer;Michal Stich.
electronic imaging (2003)
Lesion border detection in dermoscopy images.
M.Emre Celebi;Hitoshi Iyatomi;Gerald Schaefer;William V. Stoecker.
Computerized Medical Imaging and Graphics (2009)
Cost-sensitive decision tree ensembles for effective imbalanced classification
Bartosz Krawczyk;Michał Woniak;Gerald Schaefer.
soft computing (2014)
Illuminant and device invariant colour using histogram equalisation
Graham D. Finlayson;Steven D. Hordley;Gerald Schaefer;Gui Yun Tian.
Pattern Recognition (2005)
Thermography based breast cancer analysis using statistical features and fuzzy classification
Gerald Schaefer;Michal Závišek;Tomoharu Nakashima.
Pattern Recognition (2009)
Anisotropic Mean Shift Based Fuzzy C-Means Segmentation of Dermoscopy Images
Huiyu Zhou;G. Schaefer;A.H. Sadka;M.E. Celebi.
IEEE Journal of Selected Topics in Signal Processing (2009)
Solving for Colour Constancy using a Constrained Dichromatic Reflection Model
Graham D. Finlayson;Gerald Schaefer.
International Journal of Computer Vision (2001)
Lesion Border Detection in Dermoscopy Images Using Ensembles of Thresholding Methods
M. Emre Celebi;Quan Wen;Sae Hwang;Hitoshi Iyatomi.
Skin Research and Technology (2013)
Rough Sets and Near Sets in Medical Imaging: A Review
A.E. Hassanien;A. Abraham;J.F. Peters;G. Schaefer.
international conference of the ieee engineering in medicine and biology society (2009)
A Multi-Organ Nucleus Segmentation Challenge
Neeraj Kumar;Ruchika Verma;Deepak Anand;Yanning Zhou.
IEEE Transactions on Medical Imaging (2020)
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