Results 31 to 40 of about 1,014,031 (308)
Compare the performance of the models in art classification [PDF]
Because large numbers of artworks are preserved in museums and galleries, much work must be done to classify these works into genres, styles and artists. Recent technological advancements have enabled an increasing number of artworks to be digitized. Thus, it is necessary to teach computers to analyze (e.g., classify and annotate) art to assist people ...
Wentao Zhao +3 more
openaire +4 more sources
Automated Detection of Epileptic Seizures in EEG Signals via Micro-Capsule Networks
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 +4 more
doaj +1 more source
Classification of Performance and Quality Indicators in Manufacturing
A critical aspect in operations management is to represent the firm goals properly. This is usually done by translating the organisational results and objectives in ‘performance measurements'.
Franceschini, Fiorenzo +2 more
core +1 more source
Classification of Non-Civil Servant Performance Appraisal Using Naïve Bayes Classifier Algorithm
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
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. +3 more
openaire +2 more sources
Back‐dropout transfer learning for action recognition
Transfer learning aims at adapting a model learned from source dataset to target dataset. It is a beneficial approach especially when annotating on the target dataset is expensive or infeasible.
Huamin Ren +7 more
doaj +1 more source
Demographic Factors Improve Classification Performance [PDF]
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
Feature selection for modular GA-based classification
Genetic algorithms (GAs) have been used as conventional methods for classifiers to adaptively evolve solutions for classification problems. Feature selection plays an important role in finding relevant features in classification.
Guan, SU, Zhu, F, Zhu, F., Guan, S.
core +1 more source
Enhancing classification performance of multi-class imbalanced data using the OAA-DB algorithm
In data classification, the problem of imbalanced class distribution has attracted many attentions. Most efforts have used to investigate the problem mainly for binary classification.
Wong, K.W. +3 more
core +1 more source
ABSTRACT Pediatric gastroenteropancreatic neuroendocrine neoplasms (GEP‐NENs) are extremely rare and clinically heterogeneous. Management has largely been extrapolated from adult practice. This European Standard Clinical Practice Guideline (ESCP), developed by the EXPeRT network in collaboration with adult NEN experts, provides (adult) evidence ...
Michaela Kuhlen +23 more
wiley +1 more source

