What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Statistics
His primary areas of study are Artificial intelligence, Spoofing attack, Computer vision, Biometrics and Facial recognition system.
The Artificial intelligence study combines topics in areas such as Machine learning and Pattern recognition.
His Spoofing attack study combines topics in areas such as Deep learning and Face detection.
His work in the fields of Computer vision, such as Image resolution and Digital image, overlaps with other areas such as Scale.
His Biometrics study incorporates themes from Fingerprint recognition and Authentication.
Anderson Rocha interconnects Image processing, Replay attack and Computer security in the investigation of issues within Facial recognition system.
His most cited work include:
- Deep Representations for Iris, Face, and Fingerprint Spoofing Detection (307 citations)
- Vision of the unseen: Current trends and challenges in digital image and video forensics (200 citations)
- Automatic fruit and vegetable classification from images (166 citations)
What are the main themes of his work throughout his whole career to date?
Anderson Rocha spends much of his time researching Artificial intelligence, Machine learning, Computer vision, Pattern recognition and Image.
His study in Feature extraction, Biometrics, Deep learning, Facial recognition system and Face is carried out as part of his studies in Artificial intelligence.
His research in Biometrics intersects with topics in Mobile device, Spoofing attack and Authentication.
His studies in Machine learning integrate themes in fields like Classifier and Image fusion.
His work carried out in the field of Pattern recognition brings together such families of science as Contextual image classification, Bag-of-words model in computer vision, Categorization and Image processing.
His Image research integrates issues from Theoretical computer science, Information retrieval and Data mining.
He most often published in these fields:
- Artificial intelligence (65.84%)
- Machine learning (28.22%)
- Computer vision (26.73%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (65.84%)
- Machine learning (28.22%)
- Biometrics (11.39%)
In recent papers he was focusing on the following fields of study:
His main research concerns Artificial intelligence, Machine learning, Biometrics, Human–computer interaction and Task analysis.
The study incorporates disciplines such as Computer vision and Pattern recognition in addition to Artificial intelligence.
His study explores the link between Pattern recognition and topics such as Fisher vector that cross with problems in Data-driven.
His Biometrics study integrates concerns from other disciplines, such as Face, Synthetic data and Presentation.
His research integrates issues of Violence detection, Relation, Mobile device and Authentication in his study of Human–computer interaction.
His Task analysis research is multidisciplinary, relying on both Feature extraction, Prediction algorithms and Data science.
Between 2019 and 2021, his most popular works were:
- Covid-19 Automated Diagnosis and Risk Assessment through Metabolomics and Machine Learning. (4 citations)
- Survey on Reliable Deep Learning-Based Person Re-Identification Models: Are We There Yet? (4 citations)
- EMET: Embeddings from Multilingual-Encoder Transformer for Fake News Detection (4 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
Anderson Rocha focuses on Artificial intelligence, Machine learning, In patient, Computer vision and Metabolomics.
Anderson Rocha performs multidisciplinary studies into Artificial intelligence and Identity in his work.
His Maximum mean discrepancy research extends to the thematically linked field of Machine learning.
Other disciplines of study, such as Risk management, Coronavirus disease 2019, Diagnostic methods, Risk assessment and Paracoccidioidomycosis, are mixed together with his In patient studies.
His Face Presentation, Biometrics and Image study in the realm of Computer vision interacts with subjects such as Surface.
His study in Deep learning is interdisciplinary in nature, drawing from both Test, Range and Benchmark.
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