Afsham, N.
* 2014: Generalized Correlation-Based Model for Out-of-Plane Motion Estimation in Freehand Ultrasound, A
Afshang, M.[Mehrnaz]
* 2009: Gabor Filter Parameters Optimization for Texture Classification Based on Genetic Algorithm
Afshar, A.[Ahmad]
* 2017: Automatic detection and classification of the ceramic tiles' surface defects
* 2020: Diagnosis of carpal tunnel syndrome: A comparative study of shear wave elastography, morphometry and artificial intelligence techniques
* 2022: Active User Detection and Channel Estimation for Spatial-Based Random Access in Crowded Massive MIMO Systems via Blind Super-Resolution
* 2022: Crop Water Productivity Mapping and Benchmarking Using Remote Sensing and Google Earth Engine Cloud Computing
Includes: Afshar, A.[Ahmad] Afshar, A.[Ahmadreza] Afshar, A.[Abolghasem] Afshar, A.[Abbas]
Afshar, M.[Majid]
* 2019: Canadian Wetland Inventory using Google Earth Engine: The First Map and Preliminary Results
Afshar, M.H.[Mehdi H.]
* 2019: Evaluation of Remotely-Sensed and Model-Based Soil Moisture Products According to Different Soil Type, Vegetation Cover and Climate Regime Using Station-Based Observations over Turkey
* 2021: Comparative Evaluation of Microwave L-Band VOD and Optical NDVI for Agriculture Drought Detection over Central Europe
* 2021: Improving the Performance of Index Insurance Using Crop Models and Phenological Monitoring
Afshar, P.
* 2018: Brain Tumor Type Classification via Capsule Networks
* 2018: CARISI: Convolutional Autoencoder-Based Inter-Slice Interpolation of Brain Tumor Volumetric Images
* 2019: Capsule Networks' Interpretability for Brain Tumor Classification Via Radiomics Analyses
* 2019: From Handcrafted to Deep-Learning-Based Cancer Radiomics: Challenges and opportunities
* 2020: BayesCap: A Bayesian Approach to Brain Tumor Classification Using Capsule Networks
* 2020: COVID-CAPS: A capsule network-based framework for identification of COVID-19 cases from X-ray images
* 2021: Diagnosis/Prognosis of COVID-19 Chest Images via Machine Learning and Hypersignal Processing: Challenges, opportunities, and applications
* 2021: Hybrid Deep Learning Model for Diagnosis of Covid-19 Using Ct Scans and Clinical/Demographic Data
* 2021: MIXCAPS: A capsule network-based mixture of experts for lung nodule malignancy prediction
Includes: Afshar, P. Afshar, P.[Parnian]
9 for Afshar, P.
Afshar, S.
* 2016: Facial Expression Recognition in the Wild Using Improved Dense Trajectories and Fisher Vector Encoding
* 2023: Density Invariant Contrast Maximization for Neuromorphic Earth Observations
Includes: Afshar, S. Afshar, S.[Saeed]
Afshar, S.H.[Smaeil Hatefi]
* 2019: Novel Method for Improving Air Pollution Prediction Based on Machine Learning Approaches: A Case Study Applied to the Capital City of Tehran, A
Afshari, E.
* 2017: On Probability of Support Recovery for Orthogonal Matching Pursuit Using Mutual Coherence
Afshari, H.[Hossein]
* 2011: Hardware implementation of an omnidirectional camerawith real-time 3D imaging capability
* 2015: Real-Time Multiaperture Omnidirectional Visual Sensor Based on an Interconnected Network of Smart Cameras, A
Includes: Afshari, H.[Hossein] Afshari, H.
Afshari, M.[Mehdi]
* 2020: Ink Marker Segmentation in Histopathology Images Using Deep Learning
Afshari, S.[Samaneh]
* 2022: Influence of Data Density and Integration on Forest Canopy Cover Mapping Using Sentinel-1 and Sentinel-2 Time Series in Mediterranean Oak Forests, The
Afsharmanesh, H.
* 2013: Identification of Active Areas of Earthquake by Thermal Remote Sensing
Afsharnia, H.
* 2013: Evaluation and Analysis of a Parametric Approach for Simultaneous Space Resection-Intersection of High Resolution Satellite Images Without Using Ground Control Points
* 2017: Optimal Weight Design Approach for the Geometrically-Constrained Matching of Satellite Stereo Images
Includes: Afsharnia, H. Afsharnia, H.[Hamed]
Afshin Pour, B.
* 2015: Hybrid LDA+gCCA Model for fMRI Data Classification and Visualization, A
Includes: Afshin Pour, B. Afshin-Pour, B.
Afshin, M.
* 2014: Regional Assessment of Cardiac Left Ventricular Myocardial Function via MRI Statistical Features