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Bag-of-visual-words models for adult image classification and filtering

Bag-of-visual-words models for adult image classification an...

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作者： Deselaers, Thomas Pimenidis, Lexi Ney, Hermann Computer Science Department Human Language Technology and Pattern Recognition RWTH Aachen University Aachen Germany Security and Privacy Research RWTH Aachen University Aachen Germany

ISBN: (纸本)9781424421756

We present a method to classify images into different categories of pornographic content to create a system for filtering pornographic images from network traffic. Although different systems for this application were presented in the past, most of these systems are based on simple skin colour features and have rather poor performance. Recent advances in the image recognition field in particular for the classification of objects have shown that bag-of-visual-words-approaches are a good method for many image classification problems. The system we present here, is based on this approach, uses a task-specific visual vocabulary and is trained and evaluated on an image database of 8500 images from different categories. It is shown that it clearly outperforms earlier systems on this dataset and further evaluation on two novel web-traffic collections shows the good performance of the proposed system. © 2008 IEEE.

关键词： Image classification

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Crowdsourcing on Sensitive Data with Privacy-Preserving Text Rewriting 17

Crowdsourcing on Sensitive Data with Privacy-Preserving Text...

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17th Linguistic Annotation Workshop, LAW 2023, LAW 2023, co-located with ACL 2023

作者： Mouhammad, Nina Daxenberger, Johannes Schiller, Benjamin Habernal, Ivan DIPF Leibniz Institute for Research and Information in Education Germany Summetix GmbH Germany Trustworthy Human Language Technologies Department of Computer Science Technical University of Darmstadt Germany

ISBN: (纸本)9781959429838

Most tasks in NLP require labeled data. Data labeling is often done on crowdsourcing platforms due to scalability reasons. However, publishing data on public platforms can only be done if no privacy-relevant information is included. Textual data often contains sensitive information like person names or locations. In this work, we investigate how removing personally identifiable information (PII) as well as applying differential privacy (DP) rewriting can enable text with privacy-relevant information to be used for crowdsourcing. We find that DP-rewriting before crowdsourcing can preserve privacy while still leading to good label quality for certain tasks and data. PII-removal led to good label quality in all examined tasks, however, there are no privacy guarantees given. © 2023 Association for Computational Linguistics.

关键词： Crowdsourcing

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PPDB: The paraphrase database

PPDB: The paraphrase database

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2013 Conference of the North American Chapter of the Association for Computational Linguistics: human language Technologies, NAACL HLT 2013

作者： Ganitkevitch, Juri Van Durme, Benjamin Callison-Burch, Chris Center for Language and Speech Processing Johns Hopkins University United States Human Language Technology Center of Excellence Johns Hopkins University United States Computer and Information Science Department University of Pennsylvania United States

ISBN: (纸本)9781937284473

We present the 1.0 release of our paraphrase database, PPDB. Its English portion, PPDB:Eng, contains over 220 million paraphrase pairs, consisting of 73 million phrasal and 8 million lexical paraphrases, as well as 140 million paraphrase patterns, which capture many meaning-preserving syntactic transformations. The paraphrases are extracted from bilingual parallel corpora totaling over 100 million sentence pairs and over 2 billion English words. We also release PPDB:Spa, a collection of 196 million Spanish paraphrases. Each paraphrase pair in PPDB contains a set of associated scores, including paraphrase probabilities derived from the bitext data and a variety of monolingual distributional similarity scores computed from the Google n-grams and the Annotated Gigaword corpus. Our release includes pruning tools that allow users to determine their own precision/recall tradeoff. © 2013 Association for Computational Linguistics.

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Sentential paraphrasing as black-box machine translation

Sentential paraphrasing as black-box machine translation

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2016 Conference of the North American Chapter of the Association for Computational Linguistics: human language Technologies, NAACL-HLT 2016

作者： Napoles, Courtney Callison-Burch, Chris Post, Matt Center for Language and Speech Processing Johns Hopkins University United States Computer and Information Science Department University of Pennsylvania United States Human Language Technology Center of Excellence Johns Hopkins University United States

We present a simple, prepackaged solution to generating paraphrases of English sentences. We use the Paraphrase Database (PPDB) for monolingual sentence rewriting and provide machine translation language packs: Prepackaged, tuned models that can be downloaded and used to generate paraphrases on a standard Unix environment. The language packs can be treated as a black box or customized to specific tasks. In this demonstration, we will explain how to use the included interactive webbased tool to generate sentential paraphrases. © NAACL-HLT 2016 - 2016 Conference of the North American Chapter of the Association for Computational Linguistics: human language Technologies, Proceedings of the Demonstrations Session. All rights reserved.

关键词： Machine translation

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Spreading code identification of legal drones in IoT environment 8

Spreading code identification of legal drones in IoT environ...

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8th International Conference on Emerging Security Technologies, EST 2019

作者： Ali Alheeti, Khattab M. Al-Ani, Muzhir Shaban McDonald-Maier, Klaus Department of Computer Networking Systems College of Computer Science and Information Technology University of Anbar Iraq University of Human Development College of Science and Technology Department of Information Technology Sulaymaniyah Iraq School of Computer Sciences and Electronic Engineering University of Essex Colchester United Kingdom

ISBN: (纸本)9781728155463

The widespread use of drones has become very common today with large-scale civil and military applications. In the next few coming years, the outlook is expected that the number of drones will reach millions. So, these need to be well organised and managed in order to achieve the benefits of IoT with this accelerated environment. Drones or Unmanned Aerial Vehicles (UAVs) must achieved a level of communications to authenticate a legal working. The proposed approach concentrated on preparing each drone with identification key based on the combination of its international sim number with the date of the first action and the local country code. This approach is called Drone IDentification (DID) that generate a unique code for each drone via spreading technique. In this case any drone not apply this regulation is considered as unauthenticated drone and does not allowed to fly. This approach is very important to establish drone regulation via IoT. © 2019 IEEE.

关键词： Drones

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Assessing the effectiveness of computer literacy courses

Assessing the effectiveness of computer literacy courses

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2002 ASEE Annual Conference and Exposition: Vive L'ingenieur

作者： Lingard, Robert Madison, Roberta Melara, Gloria California State University Northridge Department of Computer Science Coll. of Eng. and Computer Science California State University Northridge Department of Health Sciences Coll. of Hlth. and Human Development California State University Northridge

computer literacy is growing in importance for all university students and is especially important for students pursuing technical and engineering courses of study. While an increasing number of today's students enter the university with an adequate level of computer knowledge and skill, there are many who do not. Large numbers of students, especially from economically disadvantaged communities, lack the computer skills necessary to be successful in most engineering programs. Therefore, it is particularly important for universities to offer computer literacy courses to accommodate the needs of such students. In order to ensure the effectiveness of educational programs in computer literacy, assessment must be done on a continuing basis. Such assessment has been difficult due to varying definitions of computer literacy and the lack of tools to adequately assess such programs. This paper describes a pilot study conducted at California State University, Northridge that was done as an experimental attempt to assess the effectiveness of computer literacy courses. The specific instruments used as well as others investigated are discussed, and the methods of conducting the assessment are explained. The results of the pilot study are presented along with recommendation for the development of improved instruments and methods for computer literacy assessment.

关键词： Engineering education

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PPDB: The Paraphrase Database 2

PPDB: The Paraphrase Database

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2nd Workshop on Computational Linguistics for Literature, CLfL 2013 at the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: human language Technologies, NAACL-HLT 2013

作者： Ganitkevitch, Juri van Durme, Benjamin Callison-Burch, Chris Center for Language and Speech Processing Johns Hopkins University United States Human Language Technology Center of Excellence Johns Hopkins University United States Computer and Information Science Department University of Pennsylvania United States

ISBN: (纸本)9781937284473

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FrameNet+: Fast paraphrastic tripling of FrameNet 53

FrameNet+: Fast paraphrastic tripling of FrameNet

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53rd Annual Meeting of the Association for Computational Linguistics and 7th International Joint Conference on Natural language Processing of the Asian Federation of Natural language Processing, ACL-IJCNLP 2015

作者： Pavlick, Ellie Wolfe, Travis Rastogi, Pushpendre Callison-Burch, Chris Dredze, Mark Van Durme, Benjamin Computer and Information Science Department University of Pennsylvania United States Center for Language and Speech Processing Johns Hopkins University United States Human Language Technology Center of Excellence Johns Hopkins University United States

ISBN: (纸本)9781510808461

We increase the lexical coverage of FrameNet through automatic paraphrasing. We use crowdsourcing to manually filter out bad paraphrases in order to ensure a high-precision resource. Our expanded FrameNet contains an additional 22K lexical units, a 3-fold increase over the current FrameNet, and achieves 40% better coverage when evaluated in a practical setting on New York Times data. © 2015 Association for Computational Linguistics.

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Medical Image Segmentation by Combining Adaptive Artificial Bee Colony and Wavelet Packet Decomposition 5th

Medical Image Segmentation by Combining Adaptive Artificial ...

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5th International Conference on Dependability in Sensor, Cloud, and Big Data Systems and Applications, DependSys 2019

作者： Arif, Muhammad Wang, Guojun Geman, Oana Chen, Jianer School of Computer Science Guangzhou University Guangzhou510006 China Department of Health and Human Development Stefan cel Mare University Suceava Suceava Romania

ISBN: (纸本)9789811513039

Segmentation of MRI images plays a significant and helpful job in anticipation and treatment preliminaries. Be that as it may, the power in homogeneity, sporadic fringes and one of the most exceedingly terrible pieces of the difference may cause incredible challenges in the pieces of the seeping from brain MRI images. Heaps of specialists have made in therapeutic imaging. We proposed the novel technique for image segmentation. Our technique depends on the discrete wavelet packet decomposition and ant colony optimization to reduce the disadvantage of the conventional computations in handling of the surprising shapes in restorative images preparing. To improve the exhibition of our proposed procedure we utilize the artificial bee colony to optimize and classify the feature selected or extracted by the WPD. Results shows that our method perform better to segment the curvy shapes and haemorrhagic areas in MRI images. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Magnetic resonance imaging

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Intelligent Detection System for Multi-Step Cyber-Attack Based on Machine Learning 15

Intelligent Detection System for Multi-Step Cyber-Attack Bas...

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15th International Conference on developments in eSystems Engineering, DeSE 2023

作者： Alheeti, Khattab M. Ali Alzahrani, Abdulkareem Jasim, Omar Hammad Al-Dosary, Duaa Ahmed, Hamsa M. Al-Ani, Muzhir Shaban University of Anbar Computer Networking Systems Department Ramadi Iraq Al Baha University Faculty of Computer Science and Information Technology Al Baha Saudi Arabia Human Resources Department Ramadi Iraq College of Computer Sciences and Information Technology University of Anbar Anbar Iraq University of Human Development College of Science and Technology Department of Information Technology Sulaymaniyah Iraq

ISBN: (纸本)9798350335149

Cyber-attacks involve stifling processes and activities, conciliating data, or restricting data access by carefully modifying computer systems and networks with malware. There has been a significant increase in these types of attacks over time. Due to the rise in complexity and structure, advanced defensive methods are needed. In the face of growing security threats, traditional methods of identifying cyber-attacks are ineffective. In this paper, the intelligent of intrusion a detection system is suggested. Moreover, the suggested system attempts to evaluate the capability of the k-nearest neighbour's algorithm (KNN) in terms of distinguishing between authentic and tampered data. A reliable dataset named the Multi-Step Cyber-Attack Dataset (MSCAD) is utilized to determine the behavior Among the new sorts of attacks. Moreover, 60% of the dataset was utilized for training the model, and a remaining 40% was used for testing. Evaluation metrics like accuracy, precision, recall, and F1 score are used. Experiments suggest that the proposed system-based KNN could enhance detection performance. Moreover, the suggested approach increases detection accuracy while minimizing false alarms. © 2023 IEEE.

关键词： Network security

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