Results 61 to 70 of about 2,330 (292)

Multibranch Collaboration and Segmented Training Network for Image Forgery Comprehensive Detection

IET Biometrics
With the rise of sophisticated image manipulation techniques, image detection forgeries have become increasingly challenging. This paper presents a novel deep learning framework, the multibranch collaboration and segmented training network (MBC-STN), for
Jing Chang, Jixiang Yang, Zuofan Gan, Lianjin Guo   +3 more
doaj   +1 more source

Immediate Organic Room‐Temperature Phosphorescence in Programmable Luminescent Tags Enabled by Oxygen‐Free Fabrication

Advanced Materials Technologies, EarlyView.
Programmable luminescent tags based on organic room‐temperature phosphorescence are shown to be governed by oxygen incorporation during fabrication. Oxygen‐free processing enables immediate phosphorescence activation, controlled thermal preconditioning, and tunable activation doses.
Lucy Winkler, Karl Sebastian Schellhammer, Sebastian Reineke   +2 more
wiley   +1 more source

False Matches Removing in Copy-Move Forgery Detection Algorithms

Al-Mustansiriyah Journal of Science, 2020
Today the technology age is characterized by spreading of digital images. The most common form of transfer the information in magazines, newspapers, scientific journals and all types of social media.
muthana salih mahdi, Saad N. Alsaad
doaj   +1 more source

TSPYL5 Promotes Triple‐Negative Breast Cancer Metastasis by Antagonizing USP10‐Mediated PTEN Stabilization to Unleash a ZEB1‐Dependent EMT Program

Advanced Science, EarlyView.
The hyperactivation of PI3K/AKT signaling in PTEN wild‐type triple‐negative breast cancer represents a clinical paradox. We delineate a novel post‐translational regulatory axis wherein the oncogene TSPYL5 competitively antagonizes the deubiquitinase USP10.
Jiaying Shi, Ming Yi, Shengyu Xie, Zhaokun Wang, Xinyue Zhang, Yangwei Zhang, Rui Tang, Yuan Yang, Yunqiang Liu   +8 more
wiley   +1 more source

Self-Supervised Image Local Forgery Detection by JPEG Compression Trace

, 2023
For image local forgery detection, the existing methods require a large amount of labeled data for training, and most of them cannot detect multiple types of forgery simultaneously. In this paper, we firstly analyzed the JPEG compression traces which are
Bi, Xiuli, Liu, Bo, Gao, Xinbo, Xiao, Bin, Li, Weisheng, Yan, Wuqing   +5 more
core   +1 more source

Multimodal Imaging Reveals Rapid Catecholamine Uptake and Release by Neutrophils

Advanced Science, EarlyView.
We show that immune cells (neutrophils) synthesize, uptake, and store catecholamine neurotransmitters such as dopamine or adrenaline. They also release them in response to specific stimuli (serotonin), which we directly visualize using fluorescent nanosensors. We further demonstrate that catecholamines affect neutrophil functions (NETosis) and platelet
Jennifer Mohr, Anne Schmitz, Meshkat Dinarvand, Franziska Wulfert, Sangeetha Shankar, Bjoern F. Hill, Michael Wojak, Juliana Gretz, Marie Britz, Elsa Neubert, Magdalena Shumanska, Sofia Kaushik, Linda Kartaschew, Ivan Bogeski, James Daniel, Sebastian Jung, Johannes Eble, Guido Wabnitz, Luise Erpenbeck, Sebastian Kruss   +19 more
wiley   +1 more source

SMIFD-1000 : Social media image forgery detection database

, 2022
Image forgery/manipulation is one of the most alarming topics and becomes a major concern about different social media platforms regarding one’s privacy and safety.
Rana, Md. Mehedi Rahman,, Hasnat, Abul, Rahaman, G. M. Atiqur,   +2 more
core   +1 more source

Refining PRNU-based detection of image forgeries [PDF]

2016 Digital Media Industry & Academic Forum (DMIAF), 2016
Photo Response Non-Uniformity (PRNU) noise can be considered as a spread-spectrum watermark embedded in every image taken by the source imaging device. It has been effectively used for localizing the forgeries in digital images. The noise residual extracted from the image in question is compared with the reference PRNU in a sliding-window based manner.
Xufeng Lin, Chang-Tsun Li
openaire   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Detection of Copy-Move Forgery in Digital Images Using Scale Invariant Feature Transform Algorithm and the Spearman Relationship

Iranian Journal of Electrical and Electronic Engineering, 2020
Increased popularity of digital media and image editing software has led to the spread of multimedia content forgery for various purposes. Undoubtedly, law and forensic medicine experts require trustworthy and non-forged images to enforce rights.
A. Fattahi, S. Emadi
doaj