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Open Source
Als Open Source wird Software bezeichnet, deren Quellcode öffentlich verfügbar ist und von Dritten eingesehen, genutzt und auch geändert werden darf....
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Source bias reduction for source-free domain adaptation
Source-free domain adaptation (SFDA) mainly aims to the problem of not being able to access the source domain data during the model migration...
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Header and Source Files
Our C source code can be divided into multiple files called header files and source files. These files are plain text files containing C source code....
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Who makes open source code? The hybridisation of commercial and open source practices
While Free and Open Source (F/OSS) coding has traditionally been described as a separate commons linked to values of openness and sharing, recent...
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Generation, augmentation, and alignment: a pseudo-source domain based method for source-free domain adaptation
Source-free domain adaptation (SFDA) aims to train a well-performed model in the target domain given both a trained source model and unlabeled target...
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Entropy Source Validation Certification
Entropy sources within FIPS modules require an Entropy Source Validation (ESV) certificate. This chapter describes the process for certifying an...
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Rejuvenating classical brain electrophysiology source localization methods with spatial graph Fourier filters for source extents estimation
EEG/MEG source imaging (ESI) aims to find the underlying brain sources to explain the observed EEG or MEG measurement. Multiple classical approaches...
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Source Control
If you have worked on projects in a team environment, or if you need a place to keep your own code safe, then you’ll agree that using a source...
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Source-Free Unsupervised Domain Adaptation
This chapter discusses SFDA, where models trained on labeled source data need to adapt to unlabeled target data without accessing the original source...
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Source Control with Git
Writing software often involves collaboration. This is true whether you are part of a development team, are involved in open-source projects, or are...
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A novel framework for under-determined blind source separation based on adaptive source counting using mixed linear and circular data clustering algorithm for low latency applications
Underdetermined Blind Source Separation (UBSS) refers to a general class of signal processing algorithms, aiming to recover the underlying source...
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Multi-source-free Domain Adaptive Object Detection
To enhance the transferability of object detection models in real-world scenarios where data is sampled from disparate distributions, considerable...
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Modeling source code in bimodal for program comprehension
Source code is an intermediary through which humans communicate with computer systems. It contains a large amount of domain knowledge which can be...
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Air Pollution Source Tracing Framework: Leveraging Microsensors and Wind Analysis for Pollution Source Identification
In the context of rapid urbanization, air pollution has become a significant concern, particularly in densely developed urban areas. This pollution...
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Open-Source or Freeware Tools
This chapter provides the reader with an overview to several forensic tools that are available for free use. The first sections of the chapter...
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Electronic Cash with Open-Source Observers
Electronic cash (e-cash) systems need to satisfy the property of anonymity, unforgeability, and transparency which prevent criminal activities from...
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Distributed source DOA estimation based on deep learning networks
With space electromagnetic environments becoming increasingly complex, the direction of arrival (DOA) estimation based on the point source model can...
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Forest Fire Prediction Using Multi-Source Deep Learning
Forest fire prediction is an important aspect of combating forest fires. This research focuses on the effectiveness of multi-source data (lightning,...
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A survey of multi-source image fusion
Multi-source image fusion has become an important and useful new technology in the image understanding and computer vision fields. The purpose of...
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Continual Source-Free Unsupervised Domain Adaptation
Source-free Unsupervised Domain Adaptation (SUDA) approaches inherently exhibit catastrophic forgetting. Typically, models trained on a labeled...