Results 241 to 250 of about 102,906 (305)

Is Grad-CAM Explainable in Medical Images?

International Conference on Computer Vision and Image Processing, 2023
Explainable Deep Learning has gained significant attention in the field of artificial intelligence (AI), particularly in domains such as medical imaging, where accurate and interpretable machine learning models are crucial for effective diagnosis and ...
Subhashis Suara, Aayush Jha, Pratik Sinha, A. Sekh   +3 more
semanticscholar   +1 more source

Axiom-based Grad-CAM: Towards Accurate Visualization and Explanation of CNNs

British Machine Vision Conference, 2020
To have a better understanding and usage of Convolution Neural Networks (CNNs), the visualization and interpretation of CNNs has attracted increasing attention in recent years.
Ruigang Fu, Qingyong Hu, Xiaohu Dong, Yulan Guo, Yinghui Gao, Biao Li   +5 more
semanticscholar   +1 more source

A new xAI framework with feature explainability for tumors decision-making in Ultrasound data: comparing with Grad-CAM

Comput. Methods Programs Biomed., 2023
BACKGROUND AND OBJECTIVE The value of implementing artificial intelligence (AI) on ultrasound screening for thyroid cancer has been acknowledged, with numerous early studies confirming AI might help physicians acquire more accurate diagnoses.
Di Song, Jincao Yao, Yitao Jiang, Siyuan Shi, Chen Cui, Liping Wang, Lijing Wang, Huaiyu Wu, Hongtian Tian, Xiuqin Ye, Di Ou, Wei Li, N. Feng, Weiyu Pan, Mei Song, Jinfeng Xu, Dongkui Xu, Linghu Wu, F. Dong   +18 more
semanticscholar   +1 more source

Grad-CAM (Gradient-weighted Class Activation Mapping): A systematic literature review

Computers in Biology and Medicine
Explainable Artificial Intelligence (XAI) has become a crucial aspect of modern Machine Learning (ML) and Deep Learning (DL) applications, emphasizing transparency and trust in model predictions.
Said Jadid Abdülkadir, Noureen Talpur, Shahab Ul Hassan   +2 more
exaly   +2 more sources

Caričin Grad (Yougoslavie)

Mélanges de l'Ecole française de Rome. Moyen-Age, Temps modernes, 1985
Spieser Jean-Michel, Bavant Bernard, Kondić Vladimir. Caričin Grad (Yougoslavie) . In: Mélanges de l'Ecole française de Rome. Moyen-Age, Temps modernes, tome 97, n°2. 1985. pp. 881-887.
Bavant, Bernard, Kondić, Vladimir, Spieser, Jean-Michel   +2 more
openaire   +5 more sources

Method of moments of Grad

Physical Review A, 1990
Using the kinetic theory of monatomic gases of hard-sphere particles as a base, we develop the method of moments of Grad [Commun. Pure Appl. Math 2, 331 (1949)] within the framework of algebraic computing. In this theory the basic fields are characterized by 13+9N moments of the distribution function, with 0\ensuremath{\le}N\ensuremath{\le}4.
, Reinecke, , Kremer
openaire   +2 more sources

Dendroarchaeology at Lake Ohrid: 5th and 2nd Millennia Bc Tree-Ring Chronologies from the Waterlogged Site of Ploča Mičov Grad, North Macedonia

Social Science Research Network, 2023
The prehistoric site of Ploča Mičov Grad (Ohrid,
M. Bolliger, Andrej Maczkowski, John Francuz, Johannes Reich, Marco Hostettler, A. Ballmer, G. Naumov, Bojan Taneski, V. Todoroska, Sönke Szidat, Albert Hafner   +10 more
semanticscholar   +1 more source

The New Grad

Journal for Nurses in Staff Development (JNSD), 2006
The new graduate nurse is a fragile commodity to the healthcare system and should be handled carefully to create a smooth transition to competent staff nurse. A primary role of the staff development nurse is to plan an orientation program that not only provides direction for success but is also flexible enough to meet the individual nurse's needs when ...
Katherine B, Ardoin, Susan K, Pryor
openaire   +2 more sources

IteRPrimE: Zero-shot Referring Image Segmentation with Iterative Grad-CAM Refinement and Primary Word Emphasis

AAAI Conference on Artificial Intelligence
Zero-shot Referring Image Segmentation (RIS) identifies the instance mask that best aligns with a specified referring expression without training and fine-tuning, significantly reducing the labor-intensive annotation process.
Yuji Wang, Jingchen Ni, Yong Liu, Chun Yuan, Yansong Tang   +4 more
semanticscholar   +1 more source

An Interpretability Optimization Method for Deep Learning Networks Based on Grad-CAM

IEEE Internet of Things Journal
In the modern era, the optimization of energy utilization in both industrial production and everyday life represents a critical challenge. This challenge underscores the imperative for innovative technological solutions, with artificial intelligence (AI)
Yubo Zhang, Yong Zhu, Junli Liu, Wei Yu, Chuang Jiang   +4 more
semanticscholar   +1 more source