What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
His primary areas of study are Artificial intelligence, Computer vision, Pattern recognition, Information retrieval and Image retrieval.
Artificial intelligence is closely attributed to Machine learning in his study.
His Computer vision research integrates issues from Set and Cluster analysis.
His Pattern recognition research is multidisciplinary, incorporating perspectives in Histogram, Local binary patterns, Facial expression and Robustness.
His Information retrieval research includes themes of Annotation and Principal.
His work on Visual Word and Automatic image annotation as part of general Image retrieval research is frequently linked to Function, bridging the gap between disciplines.
His most cited work include:
- Visual Information Retrieval (745 citations)
- Semantic annotation of soccer videos: automatic highlights identification (238 citations)
- 3-D Human Action Recognition by Shape Analysis of Motion Trajectories on Riemannian Manifold (229 citations)
What are the main themes of his work throughout his whole career to date?
Alberto Del Bimbo mainly investigates Artificial intelligence, Computer vision, Pattern recognition, Multimedia and Information retrieval.
In most of his Artificial intelligence studies, his work intersects topics such as Machine learning.
Three-dimensional face recognition, Video tracking, Camera resectioning, Scale-invariant feature transform and Image resolution are the core of his Computer vision study.
Alberto Del Bimbo has included themes like Histogram and Representation in his Pattern recognition study.
Alberto Del Bimbo has researched Multimedia in several fields, including World Wide Web and Human–computer interaction.
His work carried out in the field of Information retrieval brings together such families of science as Annotation and Image retrieval.
He most often published in these fields:
- Artificial intelligence (58.84%)
- Computer vision (36.59%)
- Pattern recognition (21.62%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (58.84%)
- Computer vision (36.59%)
- Pattern recognition (21.62%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Pattern recognition, Face and Machine learning.
Alberto Del Bimbo performs integrative Artificial intelligence and Trajectory research in his work.
His Computer vision research incorporates elements of Lossy compression and Metadata.
His work investigates the relationship between Pattern recognition and topics such as Image that intersect with problems in Process.
His research in Face focuses on subjects like Facial expression, which are connected to Expression.
He combines subjects such as Classifier, Recommender system, Information retrieval, Complement and Variety with his study of Artificial neural network.
Between 2018 and 2021, his most popular works were:
- Deepfake Video Detection through Optical Flow Based CNN (40 citations)
- Deep Universal Generative Adversarial Compression Artifact Removal (26 citations)
- MANTRA: Memory Augmented Networks for Multiple Trajectory Prediction (10 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
Alberto Del Bimbo mostly deals with Artificial intelligence, Pattern recognition, Machine learning, Computer vision and Face.
His Event research extends to the thematically linked field of Artificial intelligence.
His study in the fields of Convolutional neural network and Mixture model under the domain of Pattern recognition overlaps with other disciplines such as Signal processing and Sliding window protocol.
Alberto Del Bimbo studied Computer vision and Domain adaptation that intersect with Privacy preserving.
His Face study combines topics in areas such as Training set, Facial expression, Statistical model and Curvature.
The study incorporates disciplines such as Discriminative model and Image retrieval in addition to Representation.
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.
