Results 21 to 30 of about 819,529 (261)

A Fundamental Performance Limitation for Adversarial Classification [PDF]

IEEE Control Systems Letters, 2020
Despite the widespread use of machine learning algorithms to solve problems of technological, economic, and social relevance, provable guarantees on the performance of these data-driven algorithms are critically lacking, especially when the data originates from unreliable sources and is transmitted over unprotected and easily accessible channels.
Abed AlRahman Al Makdah, Vaibhav Katewa, Fabio Pasqualetti   +2 more
openaire   +2 more sources

Multi‐view learning for benign epilepsy with centrotemporal spikes

IET Computer Vision, 2019
Benign epilepsy with centrotemporal spikes (BECT) may be the most popular epilepsy to attack children. In recent years, more and more studies have shown that magnetic resonance imaging (MRI) and functional magnetic resonance imaging (fMRI) are promising ...
Ming Yan, Ling Liu, Sunitha Basodi, Yi Pan   +3 more
doaj   +1 more source

Diversified Fisher kernel: encoding discrimination in Fisher features to compete deep neural models for visual classification task

IET Computer Vision, 2020
Fisher kernels derived from stochastic probabilistic models such as restricted and deep Boltzmann machines have shown competitive visual classification results in comparison to widely popular deep discriminative models.
Sarah Ahmed, Tayyaba Azim
doaj   +1 more source

GENETIC ALGORITHM OPTIMIZATION OF FEATURE SELECTION FOR MEDICAL IMAGE CLASSIFICATION [PDF]

ICTACT Journal on Soft Computing
Medical image classification plays a pivotal role in diagnosing various diseases. However, selecting informative features from these images remains a challenging task due to the high dimensionality and complexity of the data.
Parul Saxena, M.D. Sirajul Huque, Sangeeta Vhatkar, K. Venkata Ramana, C. Anand Deva Durai   +4 more
doaj   +1 more source

The Classification Performance and Mechanism of Machine Learning Algorithms in Winter Wheat Mapping Using Sentinel-2 10 m Resolution Imagery

Applied Sciences, 2020
Machine learning algorithms are crucial for crop identification and mapping. However, many works only focus on the identification results of these algorithms, but pay less attention to their classification performance and mechanism.
Peng Fang, Xiwang Zhang, Panpan Wei, Yuanzheng Wang, Huiyi Zhang, Feng Liu, Jun Zhao   +6 more
doaj   +1 more source

Automated Detection of Epileptic Seizures in EEG Signals via Micro-Capsule Networks

Brain Sciences
Background: Epilepsy is a chronic neurological disorder that affects individuals across all age groups. Early detection and intervention are crucial for minimizing both physical and psychological distress.
Baozeng Wang, Jiayue Zhou, Hualiang Zhang, Jin Zhou, Changyong Wang   +4 more
doaj   +1 more source

Demographic Factors Improve Classification Performance [PDF]

Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), 2015
Extra-linguistic factors influence language use, and are accounted for by speakers and listeners. Most natural language processing (NLP) tasks to date, however, treat language as uniform. This assumption can harm performance. We investigate the effect of including demographic information on performance in a variety of text-classification tasks. We find
openaire   +1 more source

Predicting Stock Market Risk Using Machine Learning Classification Models

Risks
This study aims to predict stock market risk and improve preparedness for potential economic crises by identifying sharp declines in stock returns using classification-based machine learning models. Using ten years of KOSPI 200 index data (2015 to 2024),
Seol-Hyun Noh
doaj   +1 more source

Classification of Non-Civil Servant Performance Appraisal Using Naïve Bayes Classifier Algorithm

CoreID Journal, 2023
Employee performance assessment is a way to measure the level of employee productivity. In the process of assessing the performance of Non-Civil Servants (non-PNS) employees at the Regional Technical Implementation Unit of Education and Training of ...
Sofia Dewi
doaj   +1 more source

Improving BCI performance after classification

Proceedings of the 14th ACM international conference on Multimodal interaction, 2012
Brain-computer interfaces offer a valuable input modality, which unfortunately comes also with a high degree of uncertainty. There are simple methods to improve detection accuracy after the incoming brain activity has already been classified, which can be divided into (1) gathering additional evidence from other sources of information, and (2 ...
Plass - Oude Bos, D., Gürkök, Hayrettin, Reuderink, B., Poel, Mannes   +3 more
openaire   +2 more sources