What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Computer vision
- Algorithm
Beatrice Pesquet-Popescu spends much of her time researching Computer vision, Artificial intelligence, Algorithm, Motion estimation and Wavelet.
Many of her studies on Computer vision involve topics that are commonly interrelated, such as Decoding methods.
Her studies in Algorithm integrate themes in fields like Sub-band coding, Wavelet transform and Decision rule.
The various areas that Beatrice Pesquet-Popescu examines in her Wavelet transform study include Transform coding, Bitstream and Rate–distortion theory.
Her Motion estimation research includes themes of Motion vector, Reference frame and Wavelet decomposition.
Beatrice Pesquet-Popescu has included themes like Macroblock, Data compression, Theoretical computer science and Distortion minimization in her Wavelet study.
Her most cited work include:
- Three-dimensional lifting schemes for motion compensated video compression (222 citations)
- RD Optimized Coding for Motion Vector Predictor Selection (214 citations)
- Encoding method for the compression of a video sequence (174 citations)
What are the main themes of her work throughout her whole career to date?
Artificial intelligence, Computer vision, Algorithm, Wavelet and Decoding methods are her primary areas of study.
Her work carried out in the field of Artificial intelligence brings together such families of science as Coding tree unit and Pattern recognition.
She regularly ties together related areas like Codec in her Computer vision studies.
The Algorithm study combines topics in areas such as Theoretical computer science, Filter bank and Communication channel.
Her Wavelet research integrates issues from Mathematical optimization and Filter.
The concepts of her Decoding methods study are interwoven with issues in Discrete cosine transform, Encoding and Interpolation.
She most often published in these fields:
- Artificial intelligence (46.38%)
- Computer vision (41.74%)
- Algorithm (28.70%)
What were the highlights of her more recent work (between 2013-2021)?
- Artificial intelligence (46.38%)
- Computer vision (41.74%)
- Convex optimization (8.70%)
In recent papers she was focusing on the following fields of study:
Her primary areas of investigation include Artificial intelligence, Computer vision, Convex optimization, Multiview Video Coding and Data compression.
Her Artificial intelligence research is multidisciplinary, incorporating elements of Codec and Pattern recognition.
Her research in Computer vision intersects with topics in Decoding methods, Encoding and Holography.
Her Decoding methods research entails a greater understanding of Algorithm.
Her Data compression study incorporates themes from Augmented reality, Image compression and Wavelet, Wavelet transform.
Her Motion compensation research is multidisciplinary, incorporating perspectives in Motion estimation and Block-matching algorithm.
Between 2013 and 2021, her most popular works were:
- Epigraphical projection and proximal tools for solving constrained convex optimization problems (68 citations)
- A nonlocal structure tensor-based approach for multicomponent image recovery problems (56 citations)
- Initialization, Limitation, and Predictive Coding of the Depth and Texture Quadtree in 3D-HEVC (50 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Algorithm
Beatrice Pesquet-Popescu mainly investigates Computer vision, Artificial intelligence, Coding tree unit, Data compression and Holography.
Her Computer vision study integrates concerns from other disciplines, such as Decoding methods and Intra mode.
Her Artificial intelligence research is multidisciplinary, relying on both Average bitrate and Speedup.
Her Coding tree unit study also includes
- Multiview Video Coding which intersects with area such as Real-time computing and Context-adaptive binary arithmetic coding,
- Harmonic Vector Excitation Coding, which have a strong connection to Theoretical computer science, Region of interest and Coding gain.
Her research integrates issues of Lifting scheme, Augmented reality, Digital holography, Image compression and Wavelet transform in her study of Data compression.
Beatrice Pesquet-Popescu combines subjects such as Algorithm and Physical optics with her study of Wavelet transform.
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