What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Algorithm
Edward M. Riseman mainly focuses on Artificial intelligence, Image processing, Computer vision, Search engine indexing and Information retrieval.
Artificial intelligence is closely attributed to Pattern recognition in his study.
His study in the fields of Feature extraction under the domain of Pattern recognition overlaps with other disciplines such as Linear map.
His Image processing research is multidisciplinary, incorporating perspectives in Pixel and Parallel processing.
Many of his research projects under Computer vision are closely connected to Spatial query, Scale and Systems architecture with Spatial query, Scale and Systems architecture, tying the diverse disciplines of science together.
Edward M. Riseman has researched Information retrieval in several fields, including Optical character recognition, Identification, Word, Handwriting and Index.
His most cited work include:
- Extracting Straight Lines (660 citations)
- Textfinder: an automatic system to detect and recognize text in images (392 citations)
- Finding text in images (224 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Artificial intelligence, Computer vision, Image processing, Pattern recognition and Image.
His Artificial intelligence research includes elements of Machine learning and Human–computer interaction.
His work focuses on many connections between Computer vision and other disciplines, such as Computer graphics, that overlap with his field of interest in Parallax.
His research integrates issues of Image retrieval, Machine vision, Parallel processing and Search engine indexing in his study of Image processing.
His work in the fields of Pattern recognition, such as Image texture and Feature extraction, overlaps with other areas such as Context.
His research in Image tackles topics such as Computer architecture which are related to areas like SIMD.
He most often published in these fields:
- Artificial intelligence (73.25%)
- Computer vision (43.31%)
- Image processing (20.38%)
What were the highlights of his more recent work (between 1999-2008)?
- Artificial intelligence (73.25%)
- Computer vision (43.31%)
- Terrain (3.82%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Terrain, Pattern recognition and Computer graphics.
Artificial intelligence is a component of his 3D reconstruction, Image processing, Feature, Image registration and Aerial image studies.
His Image processing research incorporates themes from Machine vision and Image retrieval.
As part of one scientific family, Edward M. Riseman deals mainly with the area of Pattern recognition, narrowing it down to issues related to the Outlier, and often Basis, Data set, Feature vector, Anomaly detection and Salient.
His research investigates the connection between Computer graphics and topics such as Parallax that intersect with problems in Translation, Parallel projection, Characterization and Perspective.
His Feature extraction research is multidisciplinary, relying on both Object and Pattern recognition.
Between 1999 and 2008, his most popular works were:
- RAPID: Research on Automated Plankton Identification (175 citations)
- Generalized parallel-perspective stereo mosaics from airborne video (96 citations)
- Mobile manipulators for assisted living in residential settings (55 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Algorithm
His main research concerns Artificial intelligence, Computer vision, Image registration, Data science and Cost effectiveness.
His studies in Artificial intelligence integrate themes in fields like Surface, Residual and Parameterized complexity.
He interconnects Interpolation, Computer graphics and Pattern recognition in the investigation of issues within Computer vision.
His research in Pattern recognition intersects with topics in Object, Feature extraction and Node.
The Image registration study which covers Stereo camera that intersects with Fundamental matrix, Image stitching, Image segmentation and Stereopsis.
His studies deal with areas such as Metadata and Semantic Web as well as Data science.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
