Bicego, M.[Manuele]
* 2001: 2D shape recognition by hidden Markov models
* 2001: Designing the Minimal Structure of Hidden Markov Model by Bisimulation
* 2002: Integrated region- and pixel-based approach to background modelling
* 2003: Automatic road extraction from aerial images by probabilistic contour tracking
* 2003: sequential pruning strategy for the selection of the number of states in hidden Markov models, A
* 2003: Using hidden Markov models and wavelets for face recognition
* 2004: Audio-Video Integration for Background Modelling
* 2004: Investigating Hidden Markov Models Capabilities in 2D Shape Classification
* 2004: On-line adaptive background modelling for audio surveillance
* 2004: Similarity-Based Classification of Sequences Using Hidden Markov Models
* 2004: Statistical classification of raw textile defects
* 2005: Automatic Updating of Urban Vector Maps
* 2005: Face Authentication Using One-Class Support Vector Machines
* 2005: Hidden Markov Model approach for appearance-based 3D object recognition, A
* 2005: On Finding Differences Between Faces
* 2006: Audio-Visual Foreground Extraction for Event Characterization
* 2006: On the Use of SIFT Features for Face Authentication
* 2006: Person Authentication from Video of Faces: A Behavioral and Physiological Approach Using Pseudo Hierarchical Hidden Markov Models
* 2006: Recognizing People's Faces: from Human to Machine Vision
* 2006: Similarity-based pattern recognition
* 2006: Unsupervised scene analysis: A hidden Markov model approach
* 2007: Audio-Visual Event Recognition in Surveillance Video Sequences
* 2007: Distance Measures for Gabor Jets-Based Face Authentication: A Comparative Evaluation
* 2007: Feature Level Fusion of Face and Fingerprint Biometrics
* 2007: Generalization in Holistic versus Analytic Processing of Faces
* 2007: Recognition of Human Faces: From Biological to Artificial Vision
* 2007: Sparseness Achievement in Hidden Markov Models
* 2008: 2D Shape Classification Using Multifractional Brownian Motion
* 2008: Generalized Gaussian distributions for sequential data classification
* 2008: Hidden Markov Model Approach to Classify and Predict the Sign of Financial Local Trends, A
* 2009: 3D Face Recognition Using Joint Differential Invariants
* 2009: Clustering-Based Construction of Hidden Markov Models for Generative Kernels
* 2009: Component-Based Discriminative Classification for Hidden Markov Models
* 2009: Dynamic face recognition: From human to machine vision
* 2009: Measuring changes in face appearance through aging
* 2009: Non-linear generative embeddings for kernels on latent variable models
* 2009: On the Quantitative Estimation of Short-Term Aging in Human Faces
* 2009: Online subjective feature selection for occlusion management in tracking applications
* 2009: Soft clustering using weighted one-class support vector machines
* 2010: 2D Shape Recognition Using Information Theoretic Kernels
* 2010: Biclustering of Expression Microarray Data with Topic Models
* 2010: Combining free energy score spaces with information theoretic kernels: Application to scene classification
* 2010: Nonlinear Mappings for Generative Kernels on Latent Variable Models
* 2011: Dissimilarity-based detection of schizophrenia
* 2011: Multimodal Schizophrenia Detection by Multiclassification Analysis
* 2012: 2D shape recognition using biological sequence alignment tools
* 2012: 2D Shapes Classification Using BLAST
* 2012: Automatic Classification of Volcanic Earthquakes in HMM-Induced Vector Spaces
* 2012: Feature Selection Using Counting Grids: Application to Microarray Data
* 2013: Classification of Seismic Volcanic Signals Using Hidden-Markov-Model-Based Generative Embeddings
* 2014: Behavioural Biometrics Using Electricity Load Profiles
* 2014: Binary Factor Graph Model for Biclustering, A
* 2014: Bioinformatics Approach to 3D Shape Matching, A
* 2014: Comparison between Time-Frequency and Cepstral Feature Representations for the Classification of Seismic-Volcanic Signals, A
* 2014: Expression Microarray Data Classification Using Counting Grids and Fisher Kernel
* 2014: Metric Learning in Dissimilarity Space for Improved Nearest Neighbor Performance
* 2014: S-BLOSUM: Classification of 2D Shapes with Biological Sequence Alignment
* 2015: Volcano-Seismic Events Classification Using Document Classification Strategies
* 2016: bioinformatics approach to 2D shape classification, A
* 2016: Enriched Bag of Words for Protein Remote Homology Detection
* 2016: Multiple Structure Recovery via Probabilistic Biclustering
* 2016: Unsupervised Parameter Estimation of Non Linear Scaling for Improved Classification in the Dissimilarity Space
* 2016: Weighted K-Nearest Neighbor revisited
* 2017: biclustering approach based on factor graphs and the max-sum algorithm, A
* 2017: Dominant Set Biclustering
* 2017: Region-Based Correspondence Between 3D Shapes via Spatially Smooth Biclustering
* 2017: Spike and slab biclustering
* 2018: Clustering via binary embedding
* 2018: Mining NMR Spectroscopy Using Topic Models
* 2018: On the distinctiveness of the electricity load profile
* 2018: Protein Remote Homology Detection Using Dissimilarity-Based Multiple Instance Learning
* 2019: dissimilarity-based multiple instance learning approach for protein remote homology detection, A
* 2019: Novel Anomaly Score for Isolation Forests, A
* 2019: On the importance of local and global analysis in the judgment of similarity and dissimilarity of faces
* 2019: Relation, Transition and Comparison Between the Adaptive Nearest Neighbor Rule and the Hypersphere Classifier
* 2020: Biclustering with dominant sets
* 2021: cheaper Rectified-Nearest-Feature-Line-Segment classifier based on safe points, A
* 2021: Enhanced anomaly scores for isolation forests
* 2021: On learning Random Forests for Random Forest-clustering
* 2021: PowerHC: non linear normalization of distances for advanced nearest neighbor classification
* 2021: Proximity Isolation Forests
* 2022: Distance-Based Random Forest Clustering with Missing Data
* 2022: Using Random Forest Distances for Outlier Detection
* 2023: Active Class Selection for Dataset Acquisition in Sign Language Recognition
* 2023: Detecting outliers from pairwise proximities: Proximity isolation forests
* 2023: DisRFC: a dissimilarity-based Random Forest Clustering approach
Includes: Bicego, M.[Manuele] Bicego, M.
86 for Bicego, M.
Bicelli, A.[Alexa]
* 2022: Deep-Learning Architectures for Placenta Vessel Segmentation in TTTS Fetoscopic Images
Bicer, A.[Ali]
* 2020: Automatic grading of brain tumours using LSTM neural networks on magnetic resonance spectroscopy signals
Includes: Bicer, A.[Ali] Biçer, A.[Ali]
Bicer, B.[Berat]
* 2024: Automatic Deceit Detection Through Multimodal Analysis of High-Stake Court-Trials
Includes: Bicer, B.[Berat] Biçer, B.[Berat]
Bicer, E.[Erhan]
* 2022: Contrastive learning based facial action unit detection in children with hearing impairment for a socially assistive robot platform
Bicer, T.[Tekin]
* 2021: 3d Autoencoders for Feature Extraction In X-Ray Tomography