Brazil

A digital watermark is an information or signal inserted into a digital content (image, audio, video, document, software) that can be used to determine its ownership, showing who created or sold it, or to ensure its integrity. Typically, the same watermark is added consistently to mark movie collections. Consequently, media with a visible watermark will be eventually susceptible to the necessity of watermark remission, operation that could be an issue. This paper presents two new and very
fast algorithms for watermark detection and removal. The here considered watermarks could be blended, overlaid or added in a continuous form to the digital video on remission treatment. The first of such algorithms use a template matching approach to pre-process the blended watermarks frame-to-frame in the Hue-Saturation-Value (HSV) color space, and then improve the detection using a post-processing step. The second algorithm presents two steps as well. Initially, it estimates the structure of a translucent watermark observing the constancy of its gradient magnitude in the area corresponding to the tenth part of each video. Secondly, it uses a sliding window to detect the watermarked in the frames. The results show that watermark detection by both algorithms has high sensitivity. Moreover, they are very fast when compared with other methods especially those based on deep learning

IWSSIP 2020

Watermark Detection and Clearance in Video Using Simple Signal and Image Processing Techniques

sliding windows

digital signal

watermark

gradient

image processing

steganography

### Welcome to The 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025)

Message from the General Chair: 
*It is my great pleasure and honor to welcome you to the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), held in beautiful Vienna, Austria, from July 27 to August 1, 2025. ACL2025continues our field’s tradition of excellence in scholarship, innovation, and inclusivity, and I am deeply grateful to the many volunteers who have worked tirelessly to bring this event to life.* 
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ACL 2025

Welcome to The 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025)

technical paper

The 27th International Conference on Systems, Signals and Image Processing.

Interpretability of machine learning models: application for lawsuit prediction in the energy sector

Robust Scene Understanding Via Real-Time Approximate Bayesian Computations

Modern Architecture for Core Video Understanding

Meta-Learning Applications in Digital Image Processing

Learning to "see" touch

Biomedical Signal Processing and Analysis I

Biomedical Signal Processing and Analysis II

Signal Processing

Machine Learning & Prediction

Image-Based Detection, Recognition and Classification I

keynote

live discussion

https://d3smihljt9218e.cloudfront.net/transcript/55956/subtitle/9c226e3576aa9699d60b3ec00bb54a59.vtt

English (automatic)

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Interpretability of machine learning models: application for lawsuit prediction in the energy sector

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Efficiently Identifying Watermarked Segments in Mixed-Source Texts