What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Programming language
- Algorithm
His primary scientific interests are in Information retrieval, Artificial intelligence, Optical character recognition, Decision table and Computer vision.
His Information retrieval research includes themes of Data mining, Encoding and Cluster analysis.
In most of his Artificial intelligence studies, his work intersects topics such as Line.
The study incorporates disciplines such as Document recognition and Pattern recognition in addition to Optical character recognition.
His research in Computer vision intersects with topics in Character, Process and Error detection and correction.
His studies deal with areas such as Computer file, Connected component, Font and Pattern recognition as well as Image.
His most cited work include:
- Document search and retrieval system with partial match searching of user-drawn annotations (299 citations)
- Video user's environment (244 citations)
- Building and using a highly parallel programmable logic array (198 citations)
What are the main themes of his work throughout his whole career to date?
Daniel P. Lopresti mostly deals with Artificial intelligence, Pattern recognition, Information retrieval, Optical character recognition and Image.
The concepts of his Artificial intelligence study are interwoven with issues in Machine learning, Computer vision and Natural language processing.
His biological study spans a wide range of topics, including Process, Decoding methods and Error detection and correction.
His research integrates issues of Document layout analysis, Data mining and Database in his study of Information retrieval.
Daniel P. Lopresti has included themes like Algorithm, Approximate string matching, Character and Pattern recognition in his Optical character recognition study.
His Handwriting recognition study also includes
- Noise most often made with reference to Speech recognition,
- Biometrics and Computer security most often made with reference to Handwriting.
He most often published in these fields:
- Artificial intelligence (34.78%)
- Pattern recognition (16.09%)
- Information retrieval (12.61%)
What were the highlights of his more recent work (between 2013-2021)?
- Artificial intelligence (34.78%)
- Pattern recognition (16.09%)
- Image (10.00%)
In recent papers he was focusing on the following fields of study:
Daniel P. Lopresti mainly focuses on Artificial intelligence, Pattern recognition, Image, Psychological resilience and Pixel.
His Artificial intelligence research focuses on Deep learning, Artificial neural network, Robustness, Pattern recognition and Attention network.
His work carried out in the field of Pattern recognition brings together such families of science as Speech recognition, Document processing, Word error rate, Preprocessor and Noise.
His Pattern recognition research is multidisciplinary, incorporating perspectives in Contextual image classification and Benchmark.
His Image study incorporates themes from Range, Ground truth and Open research.
Daniel P. Lopresti has researched Pixel in several fields, including Histogram and Graph.
Between 2013 and 2021, his most popular works were:
- Systems Computing Challenges in the Internet of Things. (18 citations)
- Model-based ruling line detection in noisy handwritten documents (14 citations)
- Smart Communities Internet of Things. (12 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- The Internet
The scientist’s investigation covers issues in Computer security, Image, Internet privacy, Internet of Things and Data mining.
His work on Data security as part of general Computer security study is frequently connected to Economic impact analysis, Natural resource and Urbanization, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
The Image study combines topics in areas such as Range, Ground truth and Open research.
His Data mining research is multidisciplinary, incorporating elements of Handwriting recognition, Benchmarking, Linear regression and Handwriting.
His study on Preprocessor is covered under Artificial intelligence.
His Artificial intelligence study often links to related topics such as Speech recognition.
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.
