Results 181 to 190 of about 229,925 (327)

Traffic adversarial example attack and defense method based on explainable artificial intelligence

Tongxin xuebao
An adversarial example attack method based on XAI was proposed for AI-based NIDS. By identifying critical perturbation features with XAI and applying targeted perturbations while preserving traffic functionality, malicious traffic was gradually altered ...
MA Bowen, GUO Yuanbo, TIAN Jiwei, MA Jun, HU Yongjin   +4 more
doaj  

Secure and fault tolerant cloud based framework for medical image storage and retrieval in a distributed environment. [PDF]

Sci Rep
Amaithi Rajan A, V V, M A, R PK.
europepmc   +1 more source

Assessing the Fidelity and Utility of Water Systems Data Using Generative Adversarial Networks: A Technical Review

Md Nazmul Kabir Sikder, Yingjie Wang, Feras A. Batarseh   +2 more
openalex   +1 more source

Mining Chemical Space with Generative Models for Battery Materials

Batteries &Supercaps, EarlyView.
Revolutionizing Li‐ion battery material discovery with MatterGen, a foundational generative AI model for crystal structure inverse design. Explored stable, unique, and novel compositions and their analysis with respect to the state‐of‐the‐art databases, followed by DFT validation, provides a new direction for accelerating materials discovery ...
Chiku Parida, Diptendu Roy, Juan Maria García Lastra, Arghya Bhowmik   +3 more
wiley   +1 more source

FortiNIDS: Defending Smart City IoT Infrastructures Against Transferable Adversarial Poisoning in Machine Learning-Based Intrusion Detection Systems. [PDF]

Sensors (Basel)
Alajaji A.
europepmc   +1 more source

Generative Deep Learning for Advanced Battery Materials

Batteries &Supercaps, EarlyView.
This review explores the role of generative deep learning (DL) in battery materials analysis and highlights the fundamental principles of generative DL and its applications in designing battery materials. The importance of using multimodal data is underscored to effectively address the challenges faced during the development of battery materials across
Deepalaxmi Rajagopal, Adrian Cierpka, Britta Nestler, Arnd Koeppe   +3 more
wiley   +1 more source

Secure blockchain integrated deep learning framework for federated risk-adaptive and privacy-preserving IoT edge intelligence sets. [PDF]

Sci Rep
Swathi K, Durga P, Prasad KV, Chaitanya AK, Santhi K, Vidyullatha P, Rao SVA.   +6 more
europepmc   +1 more source

Towards Rapid Calibration of Bioprocess Quantification Models Using Single Compound Raman Spectra: A Comparison of Four Approaches

Biotechnology and Bioengineering, EarlyView.
ABSTRACT In‐line Raman spectroscopy combined with accurate quantification models can offer detailed real‐time insights into a bioprocess by monitoring key process parameters. However, traditional approaches for model calibration require extensive data collection from multiple bioreactor runs, resulting in process‐specific models that are sensitive to ...
Maarten Klaverdijk, Lisa A. Smulders, Marcel Ottens, Marieke E. Klijn   +3 more
wiley   +1 more source

Investigation of the Robustness and Transferability of Adversarial Patches in Multi-View Infrared Target Detection. [PDF]

J Imaging
Zhou Q, Zhou Z, Zhang Z, Luo W, Xiao F, Xia S, Zhu C, Wang L.   +7 more
europepmc   +1 more source

Cutting edge strategies for diabetic wound care: Nanotechnology, bioengineering, and beyond

BMEMat, EarlyView.
Graphical abstract illustrates the challenges in diabetic wound healing, covering pathophysiology, formulation hurdles, and emerging therapeutic strategies. It highlights the role of hyperglycemia, formulation complexities, and advanced technologies like bioprinting and AI in improving diabetic wound management. Abstract Diabetic wounds affect millions
Usama Ahmad, Wan Nurhidayah Wan Hanaffi, Anas Islam, Aimen Salman, Mohd Muazzam Khan, Faiyaz Shakeel, Qiang Cai, Xiaojun Cai, Quazi T. H. Shubhra   +8 more
wiley   +1 more source