Bibliografias temáticas / Splicing detection

Índice

  1. Artigos de revistas
  2. Teses / dissertações
  3. Capítulos de livros
  4. Trabalhos de conferências

Literatura científica selecionada sobre o tema "Splicing detection"

Autor: Grafiati
Publicado: 25 de janeiro de 2025

Crie uma referência precisa em APA, MLA, Chicago, Harvard, e outros estilos

Selecione um tipo de fonte:

Consulte a lista de atuais artigos, livros, teses, anais de congressos e outras fontes científicas relevantes para o tema "Splicing detection".

Ao lado de cada fonte na lista de referências, há um botão "Adicionar à bibliografia". Clique e geraremos automaticamente a citação bibliográfica do trabalho escolhido no estilo de citação de que você precisa: APA, MLA, Harvard, Chicago, Vancouver, etc.

Você também pode baixar o texto completo da publicação científica em formato .pdf e ler o resumo do trabalho online se estiver presente nos metadados.

Artigos de revistas sobre o assunto "Splicing detection"

1

Peng, Pengfei, Guoqing Liang e Tao Luan. "Multi-View Inconsistency Analysis for Video Object-Level Splicing Localization". International Journal of Emerging Technologies and Advanced Applications 1, n.º 3 (24 de abril de 2024): 1–5. http://dx.doi.org/10.62677/ijetaa.2403111.

Texto completo da fonte
Resumo:
In the digital era, the widespread use of video content has led to the rapid development of video editing technologies. However, it has also raised concerns about the authenticity and integrity of multimedia content. Video splicing forgery has emerged as a challenging and deceptive technique used to create fake video objects, potentially for malicious purposes such as deception, defamation, and fraud. Therefore, the detection of video splicing forgery has become critically important. Nevertheless, due to the complexity of video data and a lack of relevant datasets, research on video splicing forgery detection remains relatively limited. This paper introduces a novel method for detecting video object splicing forgery, which enhances detection performance by deeply exploring inconsistent features between different source videos. We incorporate various feature types, including edge luminance, texture, and video quality information, and utilize a joint learning approach with Convolutional Neural Network (CNN) and Vision Transformer (ViT) models. Experimental results demonstrate that our method excels in detecting video object splicing forgery, offering promising prospects for further advancements in this field.
Estilos ABNT, Harvard, Vancouver, APA, etc.
2

Šetrajčič Dragoš, Vita, Vida Stegel, Ana Blatnik, Gašper Klančar, Mateja Krajc e Srdjan Novaković. "New Approach for Detection of Normal Alternative Splicing Events and Aberrant Spliceogenic Transcripts with Long-Range PCR and Deep RNA Sequencing". Biology 10, n.º 8 (23 de julho de 2021): 706. http://dx.doi.org/10.3390/biology10080706.

Texto completo da fonte
Resumo:
RNA sequencing is a promising technique for detecting normal and aberrant RNA isoforms. Here, we present a new single-gene, straightforward 1-day hands-on protocol for detection of splicing alterations with deep RNA sequencing from blood. We have validated our method’s accuracy by detecting previously published normal splicing isoforms of STK11 gene. Additionally, the same technique was used to provide the first comprehensive catalogue of naturally occurring alternative splicing events of the NBN gene in blood. Furthermore, we demonstrate that our approach can be used for detection of splicing impairment caused by genetic variants. Therefore, we were able to reclassify three variants of uncertain significance: NBN:c.584G>A, STK11:c.863-5_863-3delCTC and STK11:c.615G>A. Due to the simplicity of our approach, it can be incorporated into any molecular diagnostics laboratory for determination of variant’s impact on splicing.
Estilos ABNT, Harvard, Vancouver, APA, etc.
3

Yan, Diqun, Mingyu Dong e Jinxing Gao. "Exposing Speech Transsplicing Forgery with Noise Level Inconsistency". Security and Communication Networks 2021 (27 de janeiro de 2021): 1–6. http://dx.doi.org/10.1155/2021/6659371.

Texto completo da fonte
Resumo:
Splicing is one of the most common tampering techniques for speech forgery in many forensic scenarios. Some successful approaches have been presented for detecting speech splicing when the splicing segments have different signal-to-noise ratios (SNRs). However, when the SNRs between the spliced segments are close or even same, no effective detection methods have been reported yet. In this study, noise inconsistency between the original speech and the inserted segment from other speech is utilized to detect the splicing trace. First, noise signal of the suspected speech is extracted by a parameter-optimized noise estimation algorithm. Second, the statistical Mel frequency features are extracted from the estimated noise signal. Finally, the spliced region is located by utilizing a change point detection algorithm on the estimated noise signal. The effectiveness of the proposed method is evaluated on a well-designed speech splicing dataset. The comparative experimental results show that the proposed algorithm can achieve better detection performance than other algorithms.
Estilos ABNT, Harvard, Vancouver, APA, etc.
4

Ramirez-Rodriguez, Ana Elena, Rodrigo Eduardo Arevalo-Ancona, Hector Perez-Meana, Manuel Cedillo-Hernandez e Mariko Nakano-Miyatake. "AISMSNet: Advanced Image Splicing Manipulation Identification Based on Siamese Networks". Applied Sciences 14, n.º 13 (26 de junho de 2024): 5545. http://dx.doi.org/10.3390/app14135545.

Texto completo da fonte
Resumo:
The exponential surge in specialized image editing software has intensified visual forgery, with splicing attacks emerging as a popular forgery technique. In this context, Siamese neural networks are a remarkable tool in pattern identification for detecting image manipulations. This paper introduces a deep learning approach for splicing detection based on a Siamese neural network tailored to identifying manipulated image regions. The Siamese neural network learns unique features of specific image areas and detects tampered regions through feature comparison. This architecture employs two identical branches with shared weights and image features to compare image blocks and identify tampered areas. Subsequently, a K-means algorithm is applied to identify similar centroids and determine the precise localization of duplicated regions in the image. The experimental results encompass various splicing attacks to assess effectiveness, demonstrating a high accuracy of 98.6% and a precision of 97.5% for splicing manipulation detection. This study presents an advanced splicing image forgery detection and localization algorithm, showcasing its efficacy through comprehensive experiments.
Estilos ABNT, Harvard, Vancouver, APA, etc.
5

Srinivasan, Karpagam, Lily Shiue, Justin D. Hayes, Ross Centers, Sean Fitzwater, Rebecca Loewen, Lillian R. Edmondson, Jessica Bryant, Michael Smith e Claire Rommelfanger. "Detection and measurement of alternative splicing using splicing-sensitive microarrays". Methods 37, n.º 4 (dezembro de 2005): 345–59. http://dx.doi.org/10.1016/j.ymeth.2005.09.007.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
6

Alshwely, Mohammed Kassem, e Saad N. AlSaad. "Image splicing detection based on noise level approach". Al-Mustansiriyah Journal of Science 31, n.º 4 (20 de dezembro de 2020): 55. http://dx.doi.org/10.23851/mjs.v31i4.899.

Texto completo da fonte
Resumo:
The rapid development in technology and the spread of editing image software has led to spread forgery in digital media. It is now not easy by just looking at an image to know whether the image is original or has been tampered. This article describes a new image splicing detection method based on noise level as a major feature to detect the tempered region. Principal Component Analysis (PCA) is exploited to estimate the noise of image and the K-means clustering for authentic and forged region classification. The proposed method adopts Columbia Uncompressed Image Splicing Dataset for evaluation and effectiveness. The experimental results for 360 images demonstrate that the method achieved an 83.33% for detecting tampered region this percentage represent a promising result competed with Stat-of-art splicing detection methods.
Estilos ABNT, Harvard, Vancouver, APA, etc.
7

Kadam, Kalyani Dhananjay, Swati Ahirrao e Ketan Kotecha. "Multiple Image Splicing Dataset (MISD): A Dataset for Multiple Splicing". Data 6, n.º 10 (28 de setembro de 2021): 102. http://dx.doi.org/10.3390/data6100102.

Texto completo da fonte
Resumo:
Image forgery has grown in popularity due to easy access to abundant image editing software. These forged images are so devious that it is impossible to predict with the naked eye. Such images are used to spread misleading information in society with the help of various social media platforms such as Facebook, Twitter, etc. Hence, there is an urgent need for effective forgery detection techniques. In order to validate the credibility of these techniques, publically available and more credible standard datasets are required. A few datasets are available for image splicing, such as Columbia, Carvalho, and CASIA V1.0. However, these datasets are employed for the detection of image splicing. There are also a few custom datasets available such as Modified CASIA, AbhAS, which are also employed for the detection of image splicing forgeries. A study of existing datasets used for the detection of image splicing reveals that they are limited to only image splicing and do not contain multiple spliced images. This research work presents a Multiple Image Splicing Dataset, which consists of a total of 300 multiple spliced images. We are the pioneer in developing the first publicly available Multiple Image Splicing Dataset containing high-quality, annotated, realistic multiple spliced images. In addition, we are providing a ground truth mask for these images. This dataset will open up opportunities for researchers working in this significant area.
Estilos ABNT, Harvard, Vancouver, APA, etc.
8

Su, Hang. "Image splicing detection using integrated LBP and DCT features". Applied and Computational Engineering 101, n.º 1 (8 de novembro de 2024): 71–78. http://dx.doi.org/10.54254/2755-2721/101/20240976.

Texto completo da fonte
Resumo:
Abstract. Image splicing is one of the most common techniques used for picture manipulation and forgery. With the advent of user-friendly photo editing software, image splicing has become more prevalent and increasingly difficult to detect. This paper proposes a passive photo splicing detection approach based on Local Binary Patterns (LBP) and Discrete Cosine Transform (DCT) to identify splicing forgeries. The input RGB images are first converted to the YCbCr color space. Subsequently, the chrominance channels, Cb and Cr, are divided into overlapping blocks. Each block's LBP code is then transformed into the DCT domain. For each block, the standard deviation of each DCT coefficient is computed and used as a feature. Support Vector Machine (SVM) is employed as the classifier in a predictive model to determine whether the images have been spliced. To evaluate the proposed approach, two benchmark datasets for photo tampering were utilized. Experimental results indicate that the proposed method outperforms traditional splicing detection techniques in terms of detection accuracy and performance. This enhanced detection capability underscores the potential of combining LBP and DCT features with SVM classification for robust image splicing detection, paving the way for improved digital forensics tools in combating image manipulation.
Estilos ABNT, Harvard, Vancouver, APA, etc.
9

Anna, Abramowicz, e Gos Monika. "Splicing mutations in human genetic disorders: examples, detection, and confirmation". Journal of Applied Genetics 59, n.º 3 (21 de abril de 2018): 253–68. http://dx.doi.org/10.1007/s13353-018-0444-7.

Texto completo da fonte
Resumo:
Abstract Precise pre-mRNA splicing, essential for appropriate protein translation, depends on the presence of consensus “cis” sequences that define exon-intron boundaries and regulatory sequences recognized by splicing machinery. Point mutations at these consensus sequences can cause improper exon and intron recognition and may result in the formation of an aberrant transcript of the mutated gene. The splicing mutation may occur in both introns and exons and disrupt existing splice sites or splicing regulatory sequences (intronic and exonic splicing silencers and enhancers), create new ones, or activate the cryptic ones. Usually such mutations result in errors during the splicing process and may lead to improper intron removal and thus cause alterations of the open reading frame. Recent research has underlined the abundance and importance of splicing mutations in the etiology of inherited diseases. The application of modern techniques allowed to identify synonymous and nonsynonymous variants as well as deep intronic mutations that affected pre-mRNA splicing. The bioinformatic algorithms can be applied as a tool to assess the possible effect of the identified changes. However, it should be underlined that the results of such tests are only predictive, and the exact effect of the specific mutation should be verified in functional studies. This article summarizes the current knowledge about the “splicing mutations” and methods that help to identify such changes in clinical diagnosis.
Estilos ABNT, Harvard, Vancouver, APA, etc.
10

Li, Qian, Rangding Wang e Dawen Xu. "A Video Splicing Forgery Detection and Localization Algorithm Based on Sensor Pattern Noise". Electronics 12, n.º 6 (13 de março de 2023): 1362. http://dx.doi.org/10.3390/electronics12061362.

Texto completo da fonte
Resumo:
Video splicing forgery is a common object-based intra-frame forgery operation. It refers to copying some regions, usually moving foreground objects, from one video to another. The splicing video usually contains two different modes of camera sensor pattern noise (SPN). Therefore, the SPN, which is called a camera fingerprint, can be used to detect video splicing operations. The paper proposes a video splicing detection and localization scheme based on SPN, which consists of detecting moving objects, estimating reference SPN, and calculating signed peak-to-correlation energy (SPCE). Firstly, foreground objects of the frame are extracted, and then, reference SPN are trained using frames without foreground objects. Finally, the SPCE is calculated at the block level to distinguish forged objects from normal objects. Experimental results demonstrate that the method can accurately locate the tampered area and has higher detection accuracy. In terms of accuracy and F1-score, our method achieves 0.914 and 0.912, respectively.
Estilos ABNT, Harvard, Vancouver, APA, etc.
Mais fontes

Teses / dissertações sobre o assunto "Splicing detection"

1

Sugnet, Charles W. "Discovery and detection of alternative splicing /". Diss., Digital Dissertations Database. Restricted to UC campuses, 2005. http://uclibs.org/PID/11984.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
2

Devagiri, Vishnu Manasa. "Splicing Forgery Detection and the Impact of Image Resolution". Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-14060.

Texto completo da fonte
Resumo:
Context: There has been a rise in the usage of digital images these days. Digital images are being used in many areas like in medicine, wars, etc. As the images are being used to make many important decisions, it is necessary to know if the images used are clean or forged. In this thesis, we have considered the area of splicing forgery. In this thesis, we are also considering and analyzing the impact of low-resolution images on the considered algorithms. Objectives. Through this thesis, we try to improve the detection rate of splicing forgery detection. We also examine how the examined splicing forgery detection algorithm works on low-resolution images and considered classification algorithms (classifiers). Methods: The research methods used in this research are Implementation and Experimentation. Implementation was used to answer the first research question i.e., to improve the detection rate in splicing forgery. Experimentation was used to answer the second research question. The results of the experiment were analyzed using statistical analysis to find out how the examined algorithm works on different image resolutions and on the considered classifiers. Results: One-tailed Wilcoxon signed rank test was conducted to compare which algorithm performs better, the T+ value obtained was less than To so the null hypothesis was rejected and the alternative hypothesis which states that Algorithm 2 (our enhanced version of the algorithm) performs better than Algorithm 1 (original algorithm), is accepted. Experiments were conducted and the accuracy of the algorithms in different cases were noted, ROC curves were plotted to obtain the AUC parameter. The accuracy, AUC parameters were used to determine the performance of the algorithms. Conclusions: After the results were analyzed using statistical analysis, we came to the conclusion that Algorithm 2 performs better than Algorithm 1 in detecting the forged images. It was also observed that Algorithm 1 improves its performance on low-resolution images when trained on original images and tested on images of different resolutions but, in the case of Algorithm 2, its performance is improved when trained and tested on images of the same resolution. There was not much variance in the performance of both of the algorithms on images of different resolution. Coming to the classifiers, Algorithm 1 improves its performance on linear SVM whereas Algorithm 2 improves its performance when using the simple tree classifier.
Estilos ABNT, Harvard, Vancouver, APA, etc.
3

Julliand, Thibault. "Automatic noise-based detection of splicing in digital images". Thesis, Paris Est, 2018. http://www.theses.fr/2018PESC2057.

Texto completo da fonte
Resumo:
Dans cette thèse, nous proposons trois nouvelles méthodes d’imagerie médico-légale pour détecter l’épissage dans les images numériques en exploitant les statistiques de bruit d’image. Pour ce faire, nous introduisons un nouvel outil, l’histogramme de la densité du bruit, et son dérivé, l’histogramme de la contribution de la densité du bruit. Nos méthodes permettent la détection d’épissage sur les images brutes et JPEG. Bien que l’utilisation de différences de bruit pour détecter l’épissage ait déjà été faite plusieurs fois, la plupart des méthodes existantes ont tendance à mal fonctionner sur la génération actuelle d’images de haute qualité, avec une haute résolution et faible bruit. L’efficacité de nos approches est démontrée sur un grand ensemble d’images de ce genre, avec des splicings générés aléatoirement. Nous présentons également une analyse détaillée de l’évolution du bruit dans un appareil photo numérique, et comment il affecte divers existant
In this dissertation, we offer three new forensics imagery methods to detect splicing in digital images by exploiting image noise statistics. To do so, we introduce a new tool, the noise density histogram, and its derivative, the noise density contribution histogram. Our methods allow splicing detection on both raw and JPEG images. Although the use of noise discrepancies to detect splicing has already been done multiple times, most existing methods tend to perform poorly on the current generation of high quality images, with high resolution and low noise. The effectiveness of our approaches are demonstrated over a large set of such images, with randomly-generated splicings. We also present a detailed analysis of the evolution of the noise in a digital camera, and how it affects various existing forensics approaches. In a final part, we use the tool we developed in a counter-forensics approach, in order to hide the trace left by splicing on the image noise
Estilos ABNT, Harvard, Vancouver, APA, etc.
4

Chern, Tzu-Ming. "Low detection of exon skipping in mouse genes orthologous to human genes on chromosome 22". Thesis, University of the Western Cape, 2002. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_6894_1185440491.

Texto completo da fonte
Resumo:

Alternative RNA splicing is one of the leading mechanisms contributing towards transcript and protein diversity. Several alternative splicing surveys have confirmed the frequent occurrence of exon skipping in human genes. However, the occurrence of exon skipping in mouse genes has not yet been extensively examined. Recent improvements in mouse genome sequencing have permitted the current study to explore the occurrence of exon skipping in mouse genes orthologous to human genes on chromosome 22. A low number (5/72 multi-exon genes) of mouse exon-skipped genes were captured through alignments of mouse ESTs to mouse genomic contigs. Exon-skipping events in two mouse exon-skipped genes (GNB1L, SMARCB1) appear to affect biological processes such as electron and protein transport. All mouse, skipped exons were observed to have ubiquitous tissue expression. Comparison of our mouse exon-skipping events to previously detected human exon-skipping events on chromosome 22 by Hide et al.2001, has revealed that mouse and human exon-skipping events were never observed together within an orthologous gene-pair. Although the transcript identity between mouse and human orthologous transcripts were high (greater than 80% sequence identity), the exon order in these gene-pairs may be different between mouse and human orthologous genes.

Main factors contributing towards the low detection of mouse exon-skipping events include the lack of mouse transcripts matching to mouse genomic sequences and the under-prediction of mouse exons. These factors resulted in a large number (112/269) of mouse transcripts lacking matches to mouse genomic contigs and nearly half (12/25) of the mouse multi-exon genes, which have matching Ensembl transcript identifiers, have under-predicted exons. The low frequency of mouse exon skipping on chromosome 22 cannot be extrapolated to represent a genome-wide estimate due to the small number of observed mouse exon-skipping events. However, when compared to a higher estimate (52/347) of exon skipping in human genes for chromosome 22 produced under similar conditions by Hide et al.2001, it is possible that our mouse exon-skipping frequency may be lower than the human frequency. Our hypothesis contradicts with a previous study by Brett et al.2002, in which the authors claim that mouse and human alternative splicing is comparable. Our conclusion that the mouse exon-skipping frequency may be lower than the human estimate remains to be tested with a larger mouse multi-exon gene set. However, the mouse exon-skipping frequency may represent the highest estimate that can be obtained given that the current number (87) of mouse genes orthologous to chromosome 22 in Ensembl (v1 30th Jan. 2002) does not deviate significantly from our total number (72) of mouse multi-exon genes. The quality of the current mouse genomic data is higher than the one utilized in this study. The capture of mouse exon-skipping events may increase as the quality and quantity of mouse genomic and transcript sequences improves.

Estilos ABNT, Harvard, Vancouver, APA, etc.
5

Venkatasubramanian, Meenakshi. "De novo Population Discovery from Complex Biological Datasets". University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1563873297599047.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
6

Romero, barrios Natali. "Non-codings RNAs, regulators of gene expression in Arabidopsis thaliana root developmental plasticity Noncoding Transcription by Alternative RNA Polymerases Dynamically Regulates an Auxin-Driven Chromatin Loop Battles and hijacks: noncoding transcription in plants Long noncoding RNA modulates alternative splicing regulators in Arabidopsis Detection of generic differential RNA processing events from RNA-seq data". Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLS128.

Texto completo da fonte
Resumo:
Les techniques de séquençage à haut-débit développées ces dernières années ont permis d'identifier des milliers d’ARN non-codants et des événements tels que l’épissage ou l’édition. Cette approche est à l’origine d’une meilleure compréhension des mécanismes régulant l'expression des gènes. Les longs ARN non-codants (lncARN) ont ainsi émergé comme des acteurs clés de la régulation de divers processus développementaux. Ils agissent soit directement sous leur forme longue par des interactions lncARN-protéine(s) soit après une étape de maturation qui génère des siARN ou des miARN régulateurs, menant à l’extinction génique par clivage des ARNm, la répression de la traduction ou en entrainant des modifications épigénétiques (ADN/chromatine) de leurs cibles. L’objectif de cette thèse était d’élucider les mécanismes d'action de lncARNs dans le développement de la plante. J'ai contribué à l'analyse de l'action du lncARN APOLO dans la régulation de la topologie de la chromatine chez Arabidopsis thaliana. Ensuite, j’ai concentré mes efforts sur le lncARN ASCO (Alternative Splicing COmpetitor) qui interagit avec les protéines NSRs (Nuclear Speckles RNA-binding Proteins) et participent au patron d’épissage de certains gènes cibles. Lors d’un traitement par l’auxine, NSRb est induit alors qu’ASCO est réprimé dans les racines. Le même type de traitement, chez le double mutant nsra/b et les lignées surexprimant ASCO, entraine déficience partielle dans la formation des racines latérales. En utilisant un nouvel outil bio-informatique appelé "RNAprof", nous avons détecté 1885 ARN différentiellement maturés entre le mutant nsra/b et la lignée sauvage traités à l’auxine. Parmi ces gènes, nous avons identifié ARF19, un régulateur clé de la voie de signalisation de l’auxine au cours de l'initiation et le développement de la racine. J’ai démontré qu'ARF19 interagit directement avec les NSRs et qu’il est différentiellement polyadénylé dans le double mutant nsra/b, conduisant à une isoforme plus courte du transcrit ARF19. D’autre part, parmi les gènes dérégulés de manière transcriptionnelle chez le mutant des gènes impliqués dans la signalisation par l’éthylène ont été identifiés. J’ai ensuite montré que plusieurs de ces gènes sont aussi dérégulés dans les plantes mutantes arf19-1 et arf19-2 en réponse à l’auxine, soutenant un rôle d'ARF19 dans la réponse croisée entre l’auxine et l’éthylène. Le gène NSRb est induit par l'éthylène et l'inhibition de la synthèse d'éthylène par l'AVG complémente le phénotype de racine latérale du mutant nsra/b en réponse à l’auxine. De plus, l'AVG et la surexpression d’ASCO augmentent l'accumulation de l’isoforme courte d’ARF19. Cette étude met en avant la capacité du lncARN ASCO à moduler l’épissage par le détournement des NSRs et la capacité des ARN non-codants à moduler l’épissage
In the last years, high-throughput sequencing techniques have made possible to identify thousands of noncoding RNAs and a plethora of different mRNA processing events occurring in higher organisms. This led to a better understanding of different regulatory mechanisms controlling gene expression. Long noncoding RNAs (lncRNAs) are emerging as key players in the regulation of varied developmental processes. They can act directly in a long form by lncRNA-protein interactions or be processed into shorter small si/miRNAs, leading to mRNA cleavage, translational repression or epigenetic DNA/chromatin modification of their targets. In this study, we aim to understand the mechanism of action of lncRNAs in plant development. Initially, I contributed to the analysis of the action of the APOLO lncRNA in chromatin topology regulation. Then, I focused my work on the lncRNA ASCO (Alternative Splicing COmpetitor) that interacts with NSRs (Nuclear Speckles RNA-binding Proteins) to modulate the splicing pattern of NSR-regulated mRNA targets. Auxin treatment induces NSRb and represses ASCO expression in roots. The nsra/b double mutant and ASCO overexpressing lines treated with auxin are partially impaired in lateral root formation. Using a new bioinformatic tool called “RNAprof”, we detected 1885 differential RNA processing events genome-wide in auxin-treated nsra/b mutants compared to WT. Among them, we identified ARF19, a key regulator of auxin signaling in lateral root initiation and development. I demonstrated that ARF19 is directly bound by both NSRs and that in the nsra/b double mutant ARF19 is alternatively polyadenylated leading to a short transcript isoform. Furthermore, among the transcriptionally deregulated genes in the nsra/b mutant plants, I identified an important group related to ethylene response. I further showed that several of these genes are also deregulated in the arf19-1 and arf19-2 mutants plants in response to auxin, supporting a role of ARF19 in the auxin-ethylene crosstalk. NSRb is also induced by ethylene and the inhibition of ethylene synthesis by AVG rescues the nsra/b double mutant lateral root phenotype in response to auxin. Moreover, AVG and ASCO overexpression lead to increased accumulation of the ARF19 short isoform. Altogether, this study shed new light on the role of the lncRNA ASCO in the regulation of RNA processing by hijacking NSRs and the capacity of non-coding RNAs to modulate splicing
Estilos ABNT, Harvard, Vancouver, APA, etc.
7

Abecidan, Rony. "Stratégies d'apprentissage robustes pour la détection de manipulation d'images". Electronic Thesis or Diss., Centrale Lille Institut, 2024. http://www.theses.fr/2024CLIL0025.

Texto completo da fonte
Resumo:
Aujourd'hui, la manipulation d'images à des fins non éthiques est courante, notamment sur les réseaux sociaux et dans la publicité. Les utilisateurs malveillants peuvent par exemple créer des images synthétiques convaincantes pour tromper le public ou dissimuler des messages dans des images numériques, posant des risques pour la sécurité nationale. Les chercheurs en analyse forensique d'image travaillent donc avec les forces de l'ordre pour détecter ces manipulations. Les méthodes d'analyse forensique les plus avancées utilisent notamment des réseaux neuronaux convolutifs pour les détecter. Cependant, ces réseaux sont entraînés sur des données préparées par des équipes de recherche, qui diffèrent largement des données réelles rencontrées en pratique. Cet écart réduit considérablement l'efficacité opérationnelle des détecteurs de manipulations d'images. Cette thèse vise précisément à améliorer l'efficacité des détecteurs de manipulation d'images dans un contexte pratique, en atténuant l'impact de ce décalage de données. Deux stratégies complémentaires sont explorées, toutes deux issues de la littérature en apprentissage automatique : 1. Créer des modèles capables d'apprendre à généraliser sur de nouvelles bases de données ou 2. Sélectionner, voire construire, des bases d'entraînement représentatives des images à examiner. Pour détecter des manipulations sur un grand nombre d'images non étiquetées, les stratégies d'adaptation de domaine cherchant à plonger les distributions d'entraînement et d'évaluation dans un espace latent où elles coïncident peuvent se révéler utiles. Néanmoins, on ne peut nier la faible efficacité opérationnelle de ces stratégies, étant donné qu'elles supposent un équilibre irréaliste entre images vraies et manipulées parmi les images à examiner. En plus de cette hypothèse problématique, les travaux de cette thèse montrent que ces stratégies ne fonctionnent que si la base d'entraînement guidant la détection est suffisamment proche de la base d'images sur laquelle on cherche à évaluer, une condition difficile à garantir pour un praticien. Généraliser sur un petit nombre d'images non étiquetées est encore plus difficile bien que plus réaliste. Dans la seconde partie de cette thèse, nous abordons ce scénario en examinant l'influence des opérations de développement d'images traditionnelles sur le phénomène de décalage de données en détection de manipulation d'images. Cela nous permet de formuler des stratégies pour sélectionner ou créer des bases d'entraînement adaptées à un petit nombre d'images. Notre contribution finale est une méthodologie qui exploite les propriétés statistiques des images pour construire des ensembles d'entraînement pertinents vis-à-vis des images à examiner. Cette approche réduit considérablement le problème du décalage de données et permet aux praticiens de développer des modèles sur mesure pour leur situation
Today, it is easier than ever to manipulate images for unethical purposes. This practice is therefore increasingly prevalent in social networks and advertising. Malicious users can for instance generate convincing deep fakes in a few seconds to lure a naive public. Alternatively, they can also communicate secretly hidding illegal information into images. Such abilities raise significant security concerns regarding misinformation and clandestine communications. The Forensics community thus actively collaborates with Law Enforcement Agencies worldwide to detect image manipulations. The most effective methodologies for image forensics rely heavily on convolutional neural networks meticulously trained on controlled databases. These databases are actually curated by researchers to serve specific purposes, resulting in a great disparity from the real-world datasets encountered by forensic practitioners. This data shift addresses a clear challenge for practitioners, hindering the effectiveness of standardized forensics models when applied in practical situations.Through this thesis, we aim to improve the efficiency of forensics models in practical settings, designing strategies to mitigate the impact of data shift. It starts by exploring literature on out-of-distribution generalization to find existing strategies already helping practitioners to make efficient forensic detectors in practice. Two main frameworks notably hold promise: the implementation of models inherently able to learn how to generalize on images coming from a new database, or the construction of a representative training base allowing forensics models to generalize effectively on scrutinized images. Both frameworks are covered in this manuscript. When faced with many unlabeled images to examine, domain adaptation strategies matching training and testing bases in latent spaces are designed to mitigate data shifts encountered by practitioners. Unfortunately, these strategies often fail in practice despite their theoretical efficiency, because they assume that scrutinized images are balanced, an assumption unrealistic for forensic analysts, as suspects might be for instance entirely innocent. Additionally, such strategies are tested typically assuming that an appropriate training set has been chosen from the beginning, to facilitate adaptation on the new distribution. Trying to generalize on a few images is more realistic but much more difficult by essence. We precisely deal with this scenario in the second part of this thesis, gaining a deeper understanding of data shifts in digital image forensics. Exploring the influence of traditional processing operations on the statistical properties of developed images, we formulate several strategies to select or create training databases relevant for a small amount of images under scrutiny. Our final contribution is a framework leveraging statistical properties of images to build relevant training sets for any testing set in image manipulation detection. This approach improves by far the generalization of classical steganalysis detectors on practical sets encountered by forensic analyst and can be extended to other forensic contexts
Estilos ABNT, Harvard, Vancouver, APA, etc.
8

PANT, MALLIKA. "DIGITAL SPLICING DETECTION USING LOCAL INVARIANT FEATURES". Thesis, 2016. http://dspace.dtu.ac.in:8080/jspui/handle/repository/14798.

Texto completo da fonte
Resumo:
Digital images have become the most important source of information. Due to presence of various image editing tools, images can be easily changed and altered. Therefore, the authentication of digital images has become an important issue. Forgery is performed by copying one part of an image somewhere else in same image. Copied part can be rotated, scaled or cropped while duplicating. So it is necessary to distinguish between authentic and forged images. These techniques are divided into two varieties- one being active i.e. intrusive. It means one needs to embed something in image example watermark, if the image is modified then the embedded data is also modified. Another one is passive i.e non-intrusive. It is a signature based technique. The work presents and compares feature selection algorithms for the detection of image forgery in tampered images. Various features are extracted from normal and spliced using spatial gray level dependence method and many more. Support vector machine has been used for classification. A very difficult problem in classification techniques is the choice of features to distinguish between classes. The feature optimization problem is addressed using a genetic algorithm (GA) as a search method. Classical sequential methods and floating search algorithm are compared against the genetic approach in terms of the best recognition rate achieved and the optimal number of features.
Estilos ABNT, Harvard, Vancouver, APA, etc.
9

Barros, Pedro Miguel Rodrigues de. "Alternative splicing detection across different tissues in cork oak". Master's thesis, 2017. http://hdl.handle.net/10451/31981.

Texto completo da fonte
Resumo:
Tese de mestrado, Bioinformática e Biologia Computacional (Bioinformática) Universidade de Lisboa, Faculdade de Ciências, 2017
As florestas de sobreiro (Quercus suber L.) são recursos únicos e emblemáticos em Portugal, com elevado impacto económico, ecológico e social. A disponibilidade recente da sequência do genoma de sobreiro forneceu um importante contributo para revitalizar a pesquisa em temas como desenvolvimento de cortiça e melhoramento da planta, assim como promover a competitividade da indústria da cortiça. No entanto, é ainda necessário adicionar mais detalhe à anotação estrutural do genoma, nomeadamente ao nível dos transcritos, incluindo previsão de eventos de splicing alternativo. O splicing alternativo (AS) é um processo usado durante a expressão génica que origina diferentes variantes de transcritos (isoformas) e produtos proteicos a partir um único gene. No presente estudo, procedemos à análise de dezasseis bibliotecas de RNA-seq, preparadas a partir de quatro tecidos de sobreiro (folhas, felema, entrecasco e xilema), de modo a prever novas formas de AS para genes já previstos e melhorar a anotação estrutural do genoma. Um protocolo bioinformático foi definido para testar o desempenho do software HISAT2 e STAR para mapeamento de reads de RNAseq no genoma de referência, e do software Cufflinks e StringTie para (re)construção de transcritos. O alinhamento de reads no genoma efetuado com STAR resultou em taxas de mapeamento (de 84,22% a 86,86%) superiores aos resultados atingidos com HISAT2 (73,88% a 76,55%). Assim, os resultados de mapeamento com STAR foram utilizados para a (re)construção de transcritos. O uso do StringTie para este processo foi globalmente mais conservador do que com Cufflinks, gerando menos transcritos novos, mas com melhor cobertura de reads por pares de base. Para melhorar a precisão da anotação e reduzir falsos positivos, foi realizado um passo adicional de otimização com StringTie. Desta otimização resultou uma anotação que prevê a ocorrência de 7 958 novos transcritos (8% dos transcritos totais), dos quais 5 453 são novas isoformas para genes previstos na anotação de referência. Esta nova anotação foi utilizada como referência para estimar a abundância dos transcritos em cada um dos tecidos estudados e efetuar a análise de expressão diferencial. Cerca de 16% de todos os genes expressos nos quatro tecidos e que contêm intrões apresentaram splicing alternativo, e os principais eventos de splicing foram alternative acceptor site e intron retention. Grupos de transcritos com expressão diferencial entre os quatro tecidos foram identificados e a análise de enriquecimento funcional confirmou os principais processos biológicos esperados para cada tecido: os transcritos mais expressos nas folhas e no xilema estavam relacionados com a fotossíntese e com transporte, respetivamente; transcritos mais expressos na periderme (felema e entrecasco) mostraram um enriquecimento em categorias funcionais relacionadas com a síntese de suberina e outros componentes de parede celular presentes nas células de cortiça. Estes grupos específicos mostraram também um enriquecimento em transcritos envolvidos na resposta ao stresse (biótico ou abiótico). Nos tecidos que compõem a periderme, este enriquecimento foi observado principalmente no entrecasco, enquanto que no felema foi detetado um enriquecimento em transcritos envolvidos no metabolismo secundário. A presente tese permitiu a definição de um protocolo padrão que poderá ser usado para estudar o splicing alternativo no sobreiro e para uma análise mais aprofundada na nova versão do genoma, que estará disponível em breve.
Cork oak (Quercus suber L.) forests are unique and emblematic resources for Portugal, with high economical, ecological and social significance. The recent availability of the cork oak genome sequence provided an important contribution to reinvigorate research in fundamental topics such as cork development and plant improvement, and to promote the competitiveness of cork industry. Yet, further analysis is required to add detail to genome structure annotation, namely at the transcript level, also taking into account alternative splicing. Alternative splicing (AS) is a process used during gene expression to yield different transcript variants and protein products derived from a single gene. In the present study, we analyzed sixteen RNA-seq libraries prepared from four cork oak tissues (leaf, xylem, phellem and inner bark), in order to predict new AS forms for the already predicted genes and improve genome structural annotation. A bioinformatics pipeline was defined in order to test the performance of HISAT2 and STAR for read mapping against the reference genome, and Cufflinks and StringTie for transcript assembly. STAR yielded higher mapping efficiencies (84.22% to 86.86%) for the cork oak datasets, as compared to HISAT2 (73.88% to 76.55%), and the corresponding mapping data was selected for transcript assembly. The use of StringTie for this step was globally more conservative than Cufflinks, generating less novel transcripts, but with better support by read per base coverage. A further optimization step was performed using StringTie in order to improve annotation precision. The final transcript annotation was selected from this optimization step, predicting 7,958 novel transcripts (8% of total transcripts in the new annotation), 5,453 of which were novel isoforms for genes in reference annotation. This new annotation was used as reference to estimate transcript abundance in each tissue and differential expression analysis. Approximately 16% of all intron-containing genes expressed in the four tissues were alternatively spliced and the main event found in the four cork oak tissues was alternative acceptor site, followed by intron retention. Transcript clusters showing differential expression among the four tissues were identified and functional enrichment analysis confirmed the main biological processes expected for each tissue: transcripts highly expressed in leaves and xylem were mostly related to photosynthesis and transport, respectively; transcripts highly expressed in peridermis (phellem and inner bark) showed an enrichment in functional categories related to the synthesis of suberin and other component of cork cell walls. These tissue-specific clusters also showed an enrichment in transcripts involved in the response to stress (biotic or abiotic). Yet, in peridermis, this enrichment was mostly observed in inner bark samples, while phellem samples showed an enrichment in transcripts related to secondary metabolism. This thesis allowed the definition of a standard workflow that can be used to study alternative splicing in cork oak and used for further analysis on the new improved genome version that will be available soon.
Estilos ABNT, Harvard, Vancouver, APA, etc.
10

卓宥亦, Yu-Yi Cho, e 卓宥亦. "Image Splicing Detection Using Inconsistent Multi-scale Local Noise Variances". Thesis, 2013. http://ndltd.ncl.edu.tw/handle/ygjchs.

Texto completo da fonte
Resumo:
碩士
國立臺北科技大學
電機工程系所
101
Due to the rapid development of image editing software, it becomes easy to tamper a digital image and create a fake image. One of the common and simple ways of the digital image tampering is image splicing, which is to copy a region of an image to another image, and add the contents not belonging to the original image. Therefore, the authenticity of digital image has become an important issue. Since different sources of images are productions of different sensors and post-processing, they will contain different noise levels. Based on this fact, we propose a multi-scale PCA noise level estimation algorithm to detect image splicing, and improve the detection rate of the existing works. In addition, our method can locate the tampering region by clustering the estimated noise with the integration of EGB segmentation. In the experiments, we use the Columbia uncompressed image splicing detection evaluation dataset to test our method. The experimental results show that our method can detect the image splicing robustly and accurately.
Estilos ABNT, Harvard, Vancouver, APA, etc.
Mais fontes

Capítulos de livros sobre o assunto "Splicing detection"

1

Shi, Yun Q., Chunhua Chen, Guorong Xuan e Wei Su. "Steganalysis Versus Splicing Detection". In Digital Watermarking, 158–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-92238-4_13.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
2

Kim, Namshin, e Christopher Lee. "Bioinformatics Detection of Alternative Splicing". In Bioinformatics, 179–97. Totowa, NJ: Humana Press, 2008. http://dx.doi.org/10.1007/978-1-60327-159-2_9.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
3

Zhang, Zhen, Ying Zhou, Jiquan Kang e Yuan Ren. "Study of Image Splicing Detection". In Lecture Notes in Computer Science, 1103–10. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-87442-3_136.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
4

Nagtode, Smita A., e Shrutika A. Korde. "Splicing Detection Technique for Images". In Lecture Notes on Data Engineering and Communications Technologies, 654–60. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24643-3_78.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
5

Kuroyanagi, Hidehito, Akihide Takeuchi, Takayuki Nojima e Masatoshi Hagiwara. "Single-Cell Detection of Splicing Events with Fluorescent Splicing Reporters". In Alternative pre-mRNA Splicing, 298–309. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2012. http://dx.doi.org/10.1002/9783527636778.ch28.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
6

Shen, Manli, e Michael G. Fried. "Detection of RNA-Protein Complexes by Electrophoretic Mobility Shift Assay". In Alternative pre-mRNA Splicing, 182–98. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2012. http://dx.doi.org/10.1002/9783527636778.ch17.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
7

Sapra, Aparna K., Fernando Carrillo Oesterreich, Marta Pabis, Imke Listerman, Nicole Bardehle e Karla M. Neugebauer. "Splicing Factor ChIP and ChRIP: Detection of Splicing and Splicing Factors at Genes by Chromatin Immunoprecipitation". In Alternative pre-mRNA Splicing, 416–27. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2012. http://dx.doi.org/10.1002/9783527636778.ch39.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
8

Vlachoyiannopoulos, Panayiotis G. "Detection of Autoantibodies to Extractable Cellular Antigens". In RNP Particles, Splicing and Autoimmune Diseases, 141–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-80356-7_6.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
9

Liu, Jin, Hefei Ling, Fuhao Zou e Zhengding Lu. "Image Splicing Detection Using Multi-resolution Histogram". In Advances in Multimedia Information Processing - PCM 2009, 858–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10467-1_76.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
10

Zhao, Xudong, Shilin Wang, Shenghong Li, Jianhua Li e Xiang Lin. "A Distributed Scheme for Image Splicing Detection". In Digital-Forensics and Watermarking, 314–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-43886-2_23.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.

Trabalhos de conferências sobre o assunto "Splicing detection"

1

Kanca, Elif, Tolgahan Gulsoy, Arda Ustubioglu, Beste Ustubioglu, Selen Ayas, Elif Baykal Kablan e Guzin Ulutas. "Deep Learning-Based Audio Splicing Forgery Detection Using PVTv2 Transformer". In 2024 Innovations in Intelligent Systems and Applications Conference (ASYU), 1–5. IEEE, 2024. https://doi.org/10.1109/asyu62119.2024.10757148.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
2

Moghaddasi, Zahra, Hamid A. Jalab e Rafidah Md Noor. "SVD-based image splicing detection". In 2014 International Conference on Information Technology and Multimedia (ICIMU). IEEE, 2014. http://dx.doi.org/10.1109/icimu.2014.7066598.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
3

Mushtaq, Saba, e Ajaz Hussain Mir. "Novel method for image splicing detection". In 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2014. http://dx.doi.org/10.1109/icacci.2014.6968386.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
4

Zhang, Zhen, GuangHua Wang, Yukun Bian e Zhou Yu. "A novel model for splicing detection". In 2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA). IEEE, 2010. http://dx.doi.org/10.1109/bicta.2010.5645135.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
5

Matern, Falko, Christian Riess e Marc Stamminger. "Depth Map Fingerprinting and Splicing Detection". In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020. http://dx.doi.org/10.1109/icassp40776.2020.9052979.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
6

Ustubioglu, Beste, Samet Dincer, Arda Ustubioglu e Guzin Ulutas. "ArCapsNet for Audio Splicing Forgery Detection". In 2024 47th International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2024. http://dx.doi.org/10.1109/tsp63128.2024.10605934.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
7

Jin, Wa, Weihong Bi e Guangwei Fu. "Optimal fusion offset in splicing photonic crystal fibers". In ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging, editado por Yunjiang Rao. SPIE, 2013. http://dx.doi.org/10.1117/12.2034350.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
8

Kaizhen, Zhu, e Zhen Zhang. "A Novel Algorithm of Image Splicing Detection". In 2012 International Conference on Industrial Control and Electronics Engineering (ICICEE). IEEE, 2012. http://dx.doi.org/10.1109/icicee.2012.512.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
9

Fan, Yu, Philippe Carre e Christine Fernandez-Maloigne. "Image splicing detection with local illumination estimation". In 2015 IEEE International Conference on Image Processing (ICIP). IEEE, 2015. http://dx.doi.org/10.1109/icip.2015.7351341.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
10

Zhang, Zhen, Jiquan Kang e Yuan Ren. "An Effective Algorithm of Image Splicing Detection". In 2008 International Conference on Computer Science and Software Engineering. IEEE, 2008. http://dx.doi.org/10.1109/csse.2008.1621.

Texto completo da fonte
Estilos ABNT, Harvard, Vancouver, APA, etc.
Você também pode estar interessado nas extensas listas de trabalhos sobre o assunto "Splicing detection":
Artigos de revistas Teses / dissertações
Oferecemos descontos em todos os planos premium para autores cujas obras estão incluídas em seleções literárias temáticas. Contate-nos para obter um código promocional único!

Vá para a bibliografia