Zobrazeno 1 - 10
of 4 747
pro vyhledávání: '"xAI"'
Autor:
Dost Muhammad, Malika Bendechache
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 24, Iss , Pp 542-560 (2024)
This systematic literature review examines state-of-the-art Explainable Artificial Intelligence (XAI) methods applied to medical image analysis, discussing current challenges and future research directions, and exploring evaluation metrics used to as
Externí odkaz:
https://doaj.org/article/919c157942e74315bf2f9fec3bcf7873
Autor:
Beomseok Seo, Jia Li
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Deep Neural Networks (DNNs) have achieved remarkable accuracy for numerous applications, yet their complexity often renders the explanation of predictions a challenging task. This complexity contrasts with easily interpretable statistical mo
Externí odkaz:
https://doaj.org/article/9001c0db52b143599fef7be6e87d2799
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-25 (2024)
Abstract Sentiment analysis is a pivotal tool in understanding public opinion, consumer behavior, and social trends, underpinning applications ranging from market research to political analysis. However, existing sentiment analysis models frequently
Externí odkaz:
https://doaj.org/article/42c3755db21945f6b2d56854a70e5b30
Autor:
R. Uma Maheshwari, B. Paulchamy
Publikováno v:
Automatika, Vol 65, Iss 4, Pp 1517-1532 (2024)
As deepfake technology becomes increasingly sophisticated, the proliferation of manipulated images presents a significant threat to online integrity, requiring advanced detection and mitigation strategies. Addressing this critical challenge, our stud
Externí odkaz:
https://doaj.org/article/84cc9372fbb2473cad9009e2cbd3939c
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-39 (2024)
Abstract In late 2023, the United Nations conference on climate change (COP28), which was held in Dubai, encouraged a quick move from fossil fuels to renewable energy. Solar energy is one of the most promising forms of energy that is both sustainable
Externí odkaz:
https://doaj.org/article/454ecca6808540f196021c9c73e422c2
Autor:
Shakran Mahmood, Colin Teo, Jeremy Sim, Wei Zhang, Jiang Muyun, R. Bhuvana, Kejia Teo, Tseng Tsai Yeo, Jia Lu, Balazs Gulyas, Cuntai Guan
Publikováno v:
Ibrain, Vol 10, Iss 3, Pp 245-265 (2024)
Abstract The rapid advancement of artificial intelligence (AI) has sparked renewed discussions on its trustworthiness and the concept of eXplainable AI (XAI). Recent research in neuroscience has emphasized the relevance of XAI in studying cognition.
Externí odkaz:
https://doaj.org/article/a0f4a708b0ce48b39e74f7774b86c7a4
Publikováno v:
Frontiers in Artificial Intelligence, Vol 7 (2024)
Explainable Artificial Intelligence (XAI) aims to provide insights into the inner workings and the outputs of AI systems. Recently, there's been growing recognition that explainability is inherently human-centric, tied to how people perceive explanat
Externí odkaz:
https://doaj.org/article/5f300b9368c4406ca26b865c34adebb5
Publikováno v:
Alexandria Engineering Journal, Vol 111, Iss , Pp 491-510 (2025)
The high prevalence of fraud in contemporary financial transactions necessitates advanced anomaly detection systems to address the significant imbalance between legitimate and anomalous transactions in real-time datasets. To address this issue, our s
Externí odkaz:
https://doaj.org/article/e0f8ee76776c4573bf054092e529f440
Publikováno v:
Underground Space, Vol 17, Iss , Pp 226-245 (2024)
We conducted a study to evaluate the potential and robustness of gradient boosting algorithms in rock burst assessment, established a variational autoencoder (VAE) to address the imbalance rock burst dataset, and proposed a multilevel explainable art
Externí odkaz:
https://doaj.org/article/43bd135836774e6a8f26fd3bd4cabfb7
Autor:
Haytham Elmousalami, Ibrahim Sakr
Publikováno v:
Journal of Petroleum Exploration and Production Technology, Vol 14, Iss 10, Pp 2735-2752 (2024)
Abstract Lost circulation and mud losses cause 10 to 20% of the cost of drilling operations under extreme pressure and temperature conditions. Therefore, this research introduces an integrated system for an automated lost circulation severity classif
Externí odkaz:
https://doaj.org/article/2d7ac354b794404dbc573e87205841d2