Results 81 to 90 of about 21,160 (284)

Using Feature Weights to Improve Performance of Neural Networks [PDF]

, 2011
Different features have different relevance to a particular learning problem. Some features are less relevant; while some very important. Instead of selecting the most relevant features using feature selection, an algorithm can be given this knowledge of
Iqbal, Ridwan Al
core  

Artificial Neural Network to predict mean monthly total ozone in Arosa, Switzerland

, 2006
Present study deals with the mean monthly total ozone time series over Arosa, Switzerland. The study period is 1932-1971. First of all, the total ozone time series has been identified as a complex system and then Artificial Neural Networks models in the ...
Acharya U. R., Bronnimann S., Comrie A. C., Dorling S., Gardner M., Goutami Bandyopadhyay, Kartalopoulos S. V., Monge Sanz B. M., Perez P., Staehelin J., Surajit Chattopadhyay, Varotsos C., Weiss A. K., Wilks D. S., Wolff G.   +14 more
core   +1 more source

GloPath: An Entity‐Centric Foundation Model for Glomerular Lesion Assessment and Clinicopathological Insights

Advanced Science, EarlyView.
An entity‐centric foundation model, GloPath, is introduced for comprehensive glomerular lesion assessment from routine renal biopsy images. Trained on over one million glomeruli, the framework enables robust lesion recognition, grading, and cross modality diag nosis, while uncovering large‐scale clinicopathological associations.
Qiming He, Jing Li, Tian Guan, Yifei Ma, Zimo Zhao, Yanxia Wang, Hongjing Chen, Yingming Xu, Shuang Ge, Yexing Zhang, Yizhi Wang, Xinrui Chen, Lianghui Zhu, Yiqing Liu, Qingxia Hou, Shuyan Zhao, Xiaoqin Wang, Lili Ma, Peizhen Hu, Qiang Huang, Zihan Wang, Zhiyuan Shen, Junru Cheng, Siqi Zeng, Jiurun Chen, Zhen Song, Chao He, Zhe Wang, Yonghong He   +28 more
wiley   +1 more source

Mixture of Multilayer Perceptron Regressions

Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods, 2019
This paper investigates mixture of multilayer perceptron (MLP) regressions. Although mixture of MLP regressions (MoMR) can be a strong fitting model for noisy data, the research on it has been rare. We employ soft mixture approach and use the Expectation-Maximization (EM) algorithm as a basic learning method. Our learning method goes in a double-looped
Ryohei Nakano, Seiya Satoh
openaire   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Theory of Interacting Neural Networks

, 2002
In this contribution we give an overview over recent work on the theory of interacting neural networks. The model is defined in Section 2. The typical teacher/student scenario is considered in Section 3.
Kinzel, Wolfgang
core   +1 more source

Combining Stream Mining and Neural Networks for Short Term Delay Prediction

, 2018
The systems monitoring the location of public transport vehicles rely on wireless transmission. The location readings from GPS-based devices are received with some latency caused by periodical data transmission and temporal problems preventing data ...
A Bifet, CW Tsai, N Marz, Y Qin
core   +1 more source

Customizing Tactile Sensors via Machine Learning‐Driven Inverse Design

Advanced Science, EarlyView.
ABSTRACT Replicating the sophisticated sense of touch in artificial systems requires tactile sensors with precisely tailored properties. However, manually navigating the complex microstructure‐property relationship results in inefficient and suboptimal designs.
Baocheng Wang, Depeng Kong, Zhiao He, Jikai Liang, Yuyao Lu, Zikang Deng, Honghe Li, Mengke Wang, M. Jamal Deen, Zhiqiu Ye, Shuyao Zhou, Huayong Yang, Honghao Lyu, Jun Chen, Kaichen Xu, Geng Yang   +15 more
wiley   +1 more source

On-Line Learning Theory of Soft Committee Machines with Correlated Hidden Units - Steepest Gradient Descent and Natural Gradient Descent -

, 2002
The permutation symmetry of the hidden units in multilayer perceptrons causes the saddle structure and plateaus of the learning dynamics in gradient learning methods.
Amari S., Amari S., Fukumizu K., Rattray M., Saad D., Yang H. H.   +5 more
core   +1 more source

Multilayer perceptrons and data compression

Comput. Artif. Intell., 2007
This paper investigates the feasibility of using artificial neural networks as a tool for data compression. More precisely, the paper measures compression capabilities of the standard multilayer perceptrons. An outline of a possible "neural" data compression method is given.
Manger, Robert, Puljić, Krunoslav
openaire   +3 more sources