The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Anastasios N. Venetsanopoulos sits on this spectrum.
This scientist: 539 publications — 87th percentile
87% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 1,065 publications or more.
The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Anastasios N. Venetsanopoulos sits on this spectrum.
This scientist: 67 D-Index — 85th percentile
85% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 111 D-Index or more.
His primary areas of study are Artificial intelligence, Computer vision, Pattern recognition, Image processing and Algorithm. His Artificial intelligence study incorporates themes from Machine learning and Noise. His Pattern recognition research is multidisciplinary, relying on both Regularization and Multilinear map.
Anastasios N. Venetsanopoulos interconnects Pixel, Adaptive filter and Euclidean distance in the investigation of issues within Image processing. His Adaptive filter research includes themes of Brightness and Signal processing. His biological study spans a wide range of topics, including Electronic engineering, Filter, Detector and Robustness.
His main research concerns Artificial intelligence, Computer vision, Algorithm, Pattern recognition and Image processing. Artificial intelligence connects with themes related to Filter in his study. Anastasios N. Venetsanopoulos has researched Filter in several fields, including Adaptive filter and Signal processing.
His work carried out in the field of Algorithm brings together such families of science as Digital filter, Mathematical optimization and Control theory. His Digital filter research includes elements of Electronic engineering, Finite impulse response and Realization. His Pattern recognition research incorporates elements of Facial recognition system and Machine learning.
Anastasios N. Venetsanopoulos mostly deals with Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Principal component analysis. His work in Artificial intelligence addresses subjects such as Multilinear map, which are connected to disciplines such as Projection. Anastasios N. Venetsanopoulos combines topics linked to Subspace topology with his work on Pattern recognition.
The study incorporates disciplines such as Mammography and Gait analysis in addition to Computer vision. His studies in Feature extraction integrate themes in fields like Radial basis function kernel, Support vector machine, Contextual image classification, Wavelet and Pattern recognition. While the research belongs to areas of Filter, Anastasios N. Venetsanopoulos spends his time largely on the problem of Noise, intersecting his research to questions surrounding Image processing.
Anastasios N. Venetsanopoulos spends much of his time researching Artificial intelligence, Pattern recognition, Feature extraction, Computer vision and Facial recognition system. His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning, Gait and Multilinear map. His research investigates the connection between Multilinear map and topics such as Principal component analysis that intersect with problems in Projection.
In general Pattern recognition study, his work on Multilinear principal component analysis, Radial basis function kernel, Kernel embedding of distributions and Kernel method often relates to the realm of Context, thereby connecting several areas of interest. His studies deal with areas such as Gait analysis and Matched filter as well as Computer vision. His Edge detection study combines topics in areas such as Image noise, Noise reduction, Color histogram and Robustness.
I. Pitas;A. N. Venetsanopoulos
Konstantinos N. Plataniotis;Anastasios N. Venetsanopoulos
I. Pitas;A. N. Venetsanopoulos
Juwei Lu;K.N. Plataniotis;A.N. Venetsanopoulos
Haiping Lu;K.N. Plataniotis;A.N. Venetsanopoulos
Juwei Lu;K.N. Plataniotis;A.N. Venetsanopoulos
I. Pitas;A.N. Venetsanopoulos
A. Kushki;K.N. Plataniotis;A.N. Venetsanopoulos
P.E. Trahanias;A.N. Venetsanopoulos
Haiping Lu;Konstantinos N. Plataniotis;Anastasios N. Venetsanopoulos
R. Lukac;B. Smolka;K. Martin;K.N. Plataniotis
Juwei Lu;K. N. Plataniotis;A. N. Venetsanopoulos
N. B. Karayiannis;Anastasios N. Venetsanopoulos
P.E. Trahanias;D. Karakos;A.N. Venetsanopoulos
Haiping Lu;How-Lung Eng;Cuntai Guan;Konstantinos N Plataniotis
I. Pitas;A.N. Venetsanopoulos
I. Pitas;A. Venetsanopoulos
J. Lu;K.N. Plataniotis;A.N. Venetsanopoulos;S.Z. Li
P.E. Trahanias;A.N. Venetsanopoulos
D. Androutsos;K.N. Plataniotis;A.N. Venetsanopoulos
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