Soltanalian, M.
* 2013: Joint Design of the Receive Filter and Transmit Sequence for Active Sensing
* 2014: On the Randomized Kaczmarz Algorithm
* 2020: DEEP-URL: A Model-Aware Approach to Blind Deconvolution Based on Deep Unfolded Richardson-Lucy Network
* 2021: DoA Estimation Using Low-Resolution Multi-Bit Sparse Array Measurements
* 2022: Cramér-Rao Lower Bound Optimization for Hidden Moving Target Sensing via Multi-IRS-Aided Radar
* 2022: On the Building Blocks of Sparsity Measures
* 2022: One-Bit Compressive Sensing: Can We Go Deep and Blind?
* 2023: Unfolding-Aided Bootstrapped Phase Retrieval in Optical Imaging: Explainable AI reveals new imaging frontiers
Includes: Soltanalian, M. Soltanalian, M.[Mojtaba]
8 for Soltanalian, M.
Soltanayev, S.[Shakarim]
* 2019: Training Deep Learning Based Image Denoisers From Undersampled Measurements Without Ground Truth and Without Image Prior
* 2022: NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results
Soltane, A.
* 2015: Secure transfer of medical images using hybrid encryption: Authentication, confidentiality, integrity
Soltani Farani, A.
* 2013: Visual Object Tracking VOT2013 Challenge Results, The
* 2014: Collaborating frames: Temporally weighted sparse representation for visual tracking
* 2014: Locality preserving discriminative dictionary learning
* 2014: Patchwise Joint Sparse Tracking With Occlusion Detection
* 2015: Spatial-Aware Dictionary Learning for Hyperspectral Image Classification
Includes: Soltani Farani, A. Soltani-Farani, A. Soltani-Farani, A.[Ali]
Soltani Mohammadi, I.[Iman]
* 2022: efficient six-parameter perspective motion model for VVC, An
Soltani Sarvestani, M.A.
* 2015: Batch color classification using bag of colors and discriminative sparse coding
Includes: Soltani Sarvestani, M.A. Soltani-Sarvestani, M.A.
Soltani, A.[Azam]
* 2020: Improved algorithm for multiple sclerosis diagnosis in MRI using convolutional neural network
Soltani, A.A.
* 2017: Synthesizing 3D Shapes via Modeling Multi-view Depth Maps and Silhouettes with Deep Generative Networks
Soltani, F.[Faouzi]
* 2008: OS-CFAR and CMLD threshold optimization in distributed systems using evolutionary strategies
* 2008: Robust radar detection of CA, GO and SO CFAR in Pearson measurements based on a non linear compression procedure for clutter reduction
* 2008: Threshold optimization of decentralized CFAR detection in weibull clutter using genetic algorithms
* 2009: generalized switching CFAR processor based on test cell statistics, A
* 2010: On the modelling of uncertainty in radar CFAR detection
* 2012: Optimum second threshold for the CFAR binary integrator in Pearson-distributed clutter
* 2015: Using fractal dimension to target detection in bistatic SAR data
* 2019: Performance comparison of mean-level CFAR detectors in homogeneous and non-homogeneous Weibull clutter for MIMO radars
Includes: Soltani, F.[Faouzi] Soltani, F.
8 for Soltani, F.
Soltani, H.
* 2020: Preliminary Case for Hirschman Transform Video Coding, A
Soltani, I.[Iman]
* 2023: Anomaly Detection with Domain Adaptation
Soltani, M.[Mohammadreza]
* 2021: On the Information of Feature Maps and Pruning of Deep Neural Networks
* 2021: Spatial Patterns in Actual Evapotranspiration Climatologies for Europe
* 2021: Using a Groundwater Adjusted Water Balance Approach and Copulas to Evaluate Spatial Patterns and Dependence Structures in Remote Sensing Derived Evapotranspiration Products
Includes: Soltani, M.[Mohammadreza] Soltani, M.[Mohsen]
Soltani, S.
* 1988: Survey of Thresholding Techniques, A
* 2018: Improved Estimation for Well-Logging Problems Based on Fusion of Four Types of Kalman Filters
Soltanian Zadeh, H.
* 1995: Multidimensional Nonlinear Edge-Preserving Filter for Magnetic-Resonance Image Restoration, A
* 1996: Automatic segmentation of hippocampus from brain MRI using deformable contours
* 1996: comparative analysis of neural network methodologies for segmentation of magnetic resonance images, A
* 1996: Linear filter design for CNR enhancement of MR images with multiple interfering features
* 1996: Optimal Linear Transformation for MRI Feature Extraction
* 1996: Optimal Linear Transformation for MRI Feature Extraction
* 1997: Comparative Study of Segmentation Methodologies for Magnetic Resonance Imaging, A
* 1997: Computerized Analysis of Magnetic Resonance Images
* 1997: multiresolution approach for contour extraction from brain images, A
* 2003: Activation detection in fMRI using a maximum energy ratio statistic obtained by adaptive spatial filtering
* 2003: Image Retrieval Based on Index Compressed Vector Quantization
* 2003: Image retrieval based on shape similarity by edge orientation autocorrelogram
* 2003: Multiresolution fMRI activation detection using translation invariant wavelet transform and statistical analysis based on resampling
* 2004: Comparison of multiwavelet, wavelet, Haralick, and shape features for microcalcification classification in mammograms
* 2004: Model-Independent Method for fMRI Analysis
* 2005: Radon Transform Orientation Estimation for Rotation Invariant Texture Analysis
* 2005: Rotation-Invariant Multiresolution Texture Analysis Using Radon and Wavelet Transforms
* 2007: Automated Segmentation and Classification of High Throughput Yeast Assay Spots
* 2007: Hierarchical Clustering Based on Mutual Information Maximization, A
* 2007: Shape Analysis of Stroma for Iris Recognition
* 2008: Voxel-Based Morphometric Study of Brain Regions from Magnetic Resonance Images in Temporal Lobe Epilepsy
* 2009: Gait Recognition Using Wavelet Packet Silhouette Representation and Transductive Support Vector Machines
* 2009: Noisy Iris Verification: A Modified Version of Local Intensity Variation Method
* 2010: Automatic Recognition of Five Types of White Blood Cells in Peripheral Blood
* 2010: Selection-fusion approach for classification of datasets with missing values
* 2014: Robust vehicle tracking algorithm for nighttime videos captured by fixed cameras in highly reflective environments
* 2014: Roles of Various Brain Structures on Non-Invasive Lateralization of Temporal Lobe Epilepsy
* 2015: Quantification of the CEST effect by Gaussian mixture modeling of Z-spectrum
* 2016: framework for dynamic restructuring of semantic video analysis systems based on learning attention control, A
* 2016: Fusing Iris, Palmprint and Fingerprint in a Multi-biometric Recognition System
* 2017: Classification of fNIRS based brain hemodynamic response to mental arithmetic tasks
* 2017: Multi-modal data fusion using group-structured sparse canonical correlation analysis: A simulation study
* 2017: Shape analysis of hippocampus in temporal lobe epilepsy using Signed Poisson Mapping
* 2017: Structured and Sparse Canonical Correlation Analysis as a Brain-Wide Multi-Modal Data Fusion Approach
Includes: Soltanian Zadeh, H. Soltanian-Zadeh, H. Soltanian-Zadeh, H.[Hamid]
34 for Soltanian Zadeh, H.
Soltanian Zadeh, S.[Somayyeh]
* 2022: BiconNet: An edge-preserved connectivity-based approach for salient object detection
Includes: Soltanian Zadeh, S.[Somayyeh] Soltanian-Zadeh, S.[Somayyeh]
Soltanian, M.
* 2019: Hierarchical Concept Score Postprocessing and Concept-Wise Normalization in CNN-Based Video Event Recognition
* 2020: Spatio-Temporal VLAD Encoding of Visual Events Using Temporal Ordering of the Mid-Level Deep Semantics
Soltanianzadeh, H.
* 2014: Local feature fitting active contour for segmenting vessels in angiograms
SoltaniMoghadam, S.[Saeed]
* 2023: Contemporaneous Thick- and Thin-Skinned Seismotectonics in the External Zagros: The Case of the 2021 Fin Doublet, Iran
Soltaninejad, M.
* 2020: Three Dimensional Root CT Segmentation Using Multi-Resolution Encoder-Decoder Networks
Soltaninejad, S.[Sara]
* 2020: Automated Classification of Parkinson's Disease Using Diffusion Tensor Imaging Data
Soltanizadeh, H.[Hadi]
* 2009: ICDAR 2009 Handwritten Farsi/Arabic Character Recognition Competition
Soltanmohammadi, E.
* 2013: Spectrum Sensing Over MIMO Channels Using Generalized Likelihood Ratio Tests
* 2015: Tenor: A Measure of Central Tendency for Distributed Networks
Soltanolkotabi, M.
* 2018: Accelerated Wirtinger Flow for Multiplexed Fourier Ptychographic Microscopy
* 2023: CUDA: Convolution-Based Unlearnable Datasets
Includes: Soltanolkotabi, M. Soltanolkotabi, M.[Mahdi]
Soltanpour, S.[Sima]
* 2017: High-order local normal derivative pattern (LNDP) for 3D face recognition
* 2017: Multimodal 2D-3D face recognition using local descriptors: Pyramidal shape map and structural context
* 2017: survey of local feature methods for 3D face recognition, A
* 2019: Weighted Extreme Sparse Classifier and Local Derivative Pattern for 3D Face Recognition
Soltanpur, C.
* 2019: Nonlinear MMSE Equalizer for Impulsive Noise Mitigation in OFDM-Based Communications
Soltany, M.[Milad]
* 2023: HiFormer: Hierarchical Multi-scale Representations Using Transformers for Medical Image Segmentation
Soltanzadeh, H.[Hasan]
* 2004: Recognition of Persian handwritten digits using image profiles of multiple orientations
Soltanzadeh, P.[Paria]
* 2023: Addressing the class-imbalance and class-overlap problems by a metaheuristic-based under-sampling approach
Solter, A.
* 2016: Applications Of Macro Photogrammetry In Archaeology
Soltesova, M.[Marieta]
* 2023: Old Mine Map Georeferencing: Case of Marsigli's 1696 Map of the Smolnik Mines
Includes: Soltesova, M.[Marieta] Šoltésová, M.[Marieta]
Solth, A.
* 2013: Using Harris Corners for the Retrieval of Graphs in Historical Manuscripts
Soltic, S.[Snjezana]
* 2004: Application of the CIECAM02 colour appearance model to predict the effect of gamma on the colours viewed on CRT monitors
Soltis, J.[Joseph]
* 2015: Monitoring Giraffe Behavior in Thermal Video
Soltman, J.L.[Jordan L.]
* 2016: Complementary Keypoint Descriptors
Soltoggio, A.[Andrea]
* 2024: SLoSH: Set Locality Sensitive Hashing via Sliced-Wasserstein Embeddings
Soltow, E.[Erik]
* 2015: Automatic Pose Estimation Using Contour Information from X-Ray Images
Soltwisch, V.[Victor]
* 2021: Invertible Neural Networks Versus MCMC for Posterior Reconstruction in Grazing Incidence X-ray Fluorescence
Soltysiak, M.[Marek]
* 2019: Predicting Presence of Amphibian Species Using Features Obtained from GIS and Satellite Images