The most elaborate techniques for modeling images of the human face have been developed in the field ofcomputer graphics. The most general approach, in terms of modeling all parameters explicitly, consist of a 3D mesh describing the geometry of a face andbidirectional reflectancemaps of the face ...
In recent years, it has been revealed that machine learning models can produce discriminatory predictions. Hence, fairness protection has come to play a pivotal role in machine learning. In the past, most studies on fairness protection have used traditional machine learning methods to enforce fairness...
In this Section, we give a use case of ultrasound image processing, carried out by the authors of the paper during the TAXINOMISISFootnote1project. We present the collected dataset during the project, proposed methods and obtained results. To this date, no full workflow of image processing and...
Mathematical modeling of the interaction with immediate boss The upper levels set the rules and laws for employees within the centralized structure and subordinates follow their immediate boss. By the assumption that each immediate boss is a parent node of its children, thus we can model this behav...
Furthermore, efforts have been also undertaken to investigate the potential correlation between other quality parameters of coke such as Free Swelling Index (FSI) and coal properties, utilizing machine learning techniques including the random forest and neural network [14,22]. Nonetheless, most of ...
Enhancing visual qualities of images plays very important roles in various vision and learning applications. In the past few years, both knowledge-driven maximum a posterior (MAP) with prior modelings and fully data-dependent convolutional neural network (CNN) techniques have been investigated to addr...
2017 ICCV Learning to push the limits of efficient fft-based image deconvolution Code 2017 NIPS Deep Mean-Shift Priors for Image Restoration Code 2018 ICIP Modeling Realistic Degradations in Non-Blind Deconvolution 2018 CVPR Non-blind Deblurring: Handling Kernel Uncertainty with CNNs Project page &...
LEARNING METHOD FOR A MACHINE LEARNING SYSTEM FOR DETECTING AND MODELING AN OBJECT IN AN IMAGE, CORRESPONDING COMPUTER PROGRAM PRODUCT AND DEVICEA learning method of a machine learning system carries out the steps of: obtaining augmented reality images including a real image and at least one ...
Semi-supervised learning allows us to enhance model performance using unlabeled data. Semi-supervised learning can improve performance by using both labeled and unlabeled data and has been widely studied in fields such as computer vision (Wei et al., 2018; Li et al., 2021; Zhang et al., 202...
Technological innovation has enabled the development of machine learning (ML) tools that aim to improve the practice of radiologists. In the last decade, ML applications to neuro-oncology have expanded significantly, with the pre-operative prediction of glioma grade using medical imaging as a specific...