What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Operating system
His primary scientific interests are in Artificial intelligence, Computer vision, Image processing, Digital watermarking and Pattern recognition.
His research on Artificial intelligence frequently links to adjacent areas such as Algorithm.
His Image processing study combines topics in areas such as Motion estimation, Mobile computing, Motion analysis and Digital camera.
His Digital watermarking research includes elements of Watermark, Multimedia and Digital image.
His Watermark study incorporates themes from Information hiding and Authentication.
He interconnects Transform coding and Decoding methods in the investigation of issues within Data compression.
His most cited work include:
- Image Compression Using Block Truncation Coding (782 citations)
- Perceptual watermarks for digital images and video (648 citations)
- Digital watermarking: algorithms and applications (601 citations)
What are the main themes of his work throughout his whole career to date?
Edward J. Delp mostly deals with Artificial intelligence, Computer vision, Pattern recognition, Image processing and Algorithm.
His studies in Image segmentation, Segmentation, Data compression, Image and Pixel are all subfields of Artificial intelligence research.
His studies deal with areas such as Transform coding, Real-time computing, Codec and Image compression as well as Data compression.
Motion compensation, Feature extraction, Digital watermarking, Video tracking and Image texture are the core of his Computer vision study.
His Digital watermarking study also includes
- Multimedia together with Mobile device,
- Digital image that connect with fields like Watermark.
His work carried out in the field of Algorithm brings together such families of science as Speech recognition and Coding.
He most often published in these fields:
- Artificial intelligence (55.36%)
- Computer vision (40.48%)
- Pattern recognition (17.69%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (55.36%)
- Computer vision (40.48%)
- Pattern recognition (17.69%)
In recent papers he was focusing on the following fields of study:
Edward J. Delp mainly focuses on Artificial intelligence, Computer vision, Pattern recognition, Convolutional neural network and Segmentation.
His research in Artificial intelligence focuses on subjects like Microscopy, which are connected to Image quality.
His research in Computer vision is mostly concerned with Color image.
His studies in Pattern recognition integrate themes in fields like Histogram, Process and Synthetic data.
His study in Convolutional neural network is interdisciplinary in nature, drawing from both Artificial neural network, Recurrent neural network, Data compression and System identification.
Many of his studies on Segmentation apply to Ground truth as well.
Between 2014 and 2021, his most popular works were:
- Deepfake Video Detection Using Recurrent Neural Networks (216 citations)
- First Steps Toward Camera Model Identification With Convolutional Neural Networks (134 citations)
- A Two Stream Siamese Convolutional Neural Network for Person Re-identification (131 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 vision, Convolutional neural network, Pattern recognition and Image segmentation.
His Microscopy research extends to Artificial intelligence, which is thematically connected.
In his study, Watermark, Embedding, Wiener filter, Digital camera and Digital watermarking is inextricably linked to Robustness, which falls within the broad field of Computer vision.
His Pattern recognition research is multidisciplinary, incorporating perspectives in Matching, Histogram, Detector and Image retrieval.
The concepts of his Image segmentation study are interwoven with issues in Midpoint, Information retrieval and Dietary assessment.
His Image processing course of study focuses on Synthetic data and Process.
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