What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Operating system
Reiner Eschbach mainly investigates Computer vision, Artificial intelligence, Pixel, Image and Color histogram.
His studies in Computer vision integrate themes in fields like Signal and Pattern recognition.
In his works, Reiner Eschbach performs multidisciplinary study on Artificial intelligence and Variable.
The study incorporates disciplines such as Non-local means, Algorithm, Quantization, Edge enhancement and Bitmap in addition to Pixel.
His study on Halftone and Image capture is often connected to Basis as part of broader study in Image.
His work in Color histogram addresses subjects such as Adaptive histogram equalization, which are connected to disciplines such as Color normalization.
His most cited work include:
- Automatic image cropping (142 citations)
- Image-dependent sharpness enhancement (138 citations)
- Image-dependent luminance enhancement (115 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Artificial intelligence, Computer vision, Image, Pixel and Computer graphics.
His studies deal with areas such as Process, Signal and Pattern recognition as well as Artificial intelligence.
His Color image, Image processing, Halftone, Color space and Binary image study are his primary interests in Computer vision.
His Image research is multidisciplinary, incorporating elements of Function and Filter.
His biological study spans a wide range of topics, including Luminance, Gamut, Error diffusion, Binary number and Algorithm.
His Computer graphics research is mostly focused on the topic Rendering.
He most often published in these fields:
- Artificial intelligence (58.79%)
- Computer vision (54.85%)
- Image (22.12%)
What were the highlights of his more recent work (between 2013-2019)?
- Artificial intelligence (58.79%)
- Computer vision (54.85%)
- Computer graphics (15.45%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Computer vision, Computer graphics, Engineering drawing and Substrate.
His Encoding study, which is part of a larger body of work in Artificial intelligence, is frequently linked to User input, bridging the gap between disciplines.
His Computer vision study combines topics in areas such as Content, Three dimensional printing and Scanner.
The various areas that Reiner Eschbach examines in his Computer graphics study include Pixel, Coding, Feature and Font.
His Engineering drawing research incorporates themes from Confidence map, Field and Selection.
In his work, Secure copy is strongly intertwined with Watermark, which is a subfield of Substrate.
Between 2013 and 2019, his most popular works were:
- Automated form fill-in via form retrieval (31 citations)
- Method and system for controlling access to document data using augmented reality marker (18 citations)
- Anti-counterfeiting measures for three dimensional objects (9 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Operating system
His primary areas of study are Artificial intelligence, Computer graphics, Computer vision, Object and Certification.
His studies deal with areas such as Pattern recognition and Barcode as well as Artificial intelligence.
Reiner Eschbach has included themes like Watermark, Pixel and Content in his Computer graphics study.
Reiner Eschbach combines topics linked to Pantograph with his work on Pixel.
His research in the fields of Image overlaps with other disciplines such as Authentication server.
His Object research incorporates themes from Data file, Three dimensional printing, Engineering drawing and Measure.
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