Model-based deep transfer learning is arguably the most frequently used method. However, very little work has been devoted to enhancing deep transfer learning by focusing on the influence of...关键词: Computer Science - Machine Learning DOI: 10.48550/arXiv.1708.07747 被引量: 411 ...
Digital image processing is the use of algorithms to make computers analyze the content of digital images. Here are 20,072 public repositories matching this topic... Language:All Sort:Most stars Open Source Computer Vision Library opencvc-plus-pluscomputer-visiondeep-learningimage-processing ...
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...
& Miao, J. A streaming multi-GPU implementation of image simulation algorithms for scanning transmission electron microscopy. Adv. Struct. Chem. Imag. 3, 15 (2017). Article Google Scholar Barthel, J. Dr. Probe: a software for high-resolution STEM image simulation. Ultramicroscopy 193, 1–11...
Anatomy-specific automated segmentation tools for ankle, CMF, heart, hip, knee, shoulder, and spine data using Machine Learning (ML) algorithms, and automatically identifies common key landmarks. More Information SURFACE TOOLS Working with Computer-Aided Design (CAD) ...
The BoW technique has been introduced in this tutorial as applied to modeling text with machine learning algorithms. Nonetheless, this technique can also be applied to computer vision, where images are treated as visual words from which features can be extracted. For this reason, when applied to...
Mahesh B (2020) Machine learning algorithms-a review. IJSR 9:381–386 Google Scholar Mai S, Hu H, Xu J (2019) Attentive matching network for few-shot learning. Comput Vis Image Underst 187(102):781 Google Scholar Mangla P, Singh M, Sinha A et al (2020) Charting the right manifold:...
In addition, future work can study the hybridization of the original HBO with other metaheuristic or machine learning algorithms to automate the search process for the optimal number of thresholds in a specific image.Data availability All data generated or analysed during this study are included in ...
Kalluri et al. [9] combined semi-supervised learning with unsupervised domain adaptation. Stekovic et al. [10] implemented geometric constraints between multiple views of a three-dimensional (3D) scene. Consistency regularization [4], which represents a class of semi-supervised learning algorithms ...
Machine learning (ML) algorithms, particularly convolutional neural networks (CNNs), have shown promising results in medical image segmentation and have been applied to polyp detection and segmentation4,5. While deep learning (DL) algorithms can achieve high precision, they typically require large amou...