nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
1 |
ABC: Artificial Intelligence for Bladder Cancer grading system
|
Habibi, Khashayar |
|
|
9 |
C |
p. |
artikel |
2 |
A climate classification for corrosion control in electronic system design
|
Spooner, Max |
|
|
9 |
C |
p. |
artikel |
3 |
A deep convolutional neural network-based approach for detecting burn severity from skin burn images
|
Suha, Sayma Alam |
|
|
9 |
C |
p. |
artikel |
4 |
A metaheuristic with a neural surrogate function for Word Sense Disambiguation
|
Nodehi, Azim Keshavarzian |
|
|
9 |
C |
p. |
artikel |
5 |
Analysis of the performance of feature optimization techniques for the diagnosis of machine learning-based chronic kidney disease
|
Hossain, Muhammad Minoar |
|
|
9 |
C |
p. |
artikel |
6 |
Application of the VNS heuristic for feature selection in credit scoring problems
|
Helder, Victor Gomes |
|
|
9 |
C |
p. |
artikel |
7 |
A semi-supervised learning approach for bladder cancer grading
|
Wenger, Kenneth |
|
|
9 |
C |
p. |
artikel |
8 |
Autohighlight: Highlight detection in League of Legends esports broadcasts via crowd-sourced data
|
Ringer, Charles |
|
|
9 |
C |
p. |
artikel |
9 |
Bankruptcy prediction using synthetic sampling
|
Garcia, John |
|
|
9 |
C |
p. |
artikel |
10 |
Behavior prediction based on a Commodity Utility-Behavior Sequence model
|
Chen, Li |
|
|
9 |
C |
p. |
artikel |
11 |
Compressed video ensemble based pseudo-labeling for semi-supervised action recognition
|
Terao, Hayato |
|
|
9 |
C |
p. |
artikel |
12 |
Convolutional Neural Networks for vehicle damage detection
|
van Ruitenbeek, R.E. |
|
|
9 |
C |
p. |
artikel |
13 |
Cross-device behavioral consistency: Benchmarking and implications for effective android malware detection
|
Guerra-Manzanares, Alejandro |
|
|
9 |
C |
p. |
artikel |
14 |
Deep attention-based neural networks for explainable heart sound classification
|
Ren, Zhao |
|
|
9 |
C |
p. |
artikel |
15 |
Distinctive features of nonverbal behavior and mimicry in application interviews through data analysis and machine learning
|
Roegiers, Sanne |
|
|
9 |
C |
p. |
artikel |
16 |
Exact Shapley values for local and model-true explanations of decision tree ensembles
|
Campbell, Thomas W. |
|
|
9 |
C |
p. |
artikel |
17 |
Forecasting Bitcoin price direction with random forests: How important are interest rates, inflation, and market volatility?
|
Basher, Syed Abul |
|
|
9 |
C |
p. |
artikel |
18 |
Hourly electricity price forecasting with NARMAX
|
McHugh, Catherine |
|
|
9 |
C |
p. |
artikel |
19 |
Hybrid U-Net: Semantic segmentation of high-resolution satellite images to detect war destruction
|
Nabiee, Shima |
|
|
9 |
C |
p. |
artikel |
20 |
Intelligent sampling for surrogate modeling, hyperparameter optimization, and data analysis
|
Kamath, Chandrika |
|
|
9 |
C |
p. |
artikel |
21 |
Jasmine: A new Active Learning approach to combat cybercrime
|
Klein, Jan |
|
|
9 |
C |
p. |
artikel |
22 |
Machine learning approaches for predicting the onset time of the adverse drug events in oncology
|
Timilsina, Mohan |
|
|
9 |
C |
p. |
artikel |
23 |
Machine-learning models for spatially-explicit forecasting of future racial segregation in US cities
|
Stepinski, Tomasz F. |
|
|
9 |
C |
p. |
artikel |
24 |
Mining commit messages to enhance software refactorings recommendation: A machine learning approach
|
Nyamawe, Ally S. |
|
|
9 |
C |
p. |
artikel |
25 |
MLPro 1.0 - Standardized reinforcement learning and game theory in Python
|
Arend, Detlef |
|
|
9 |
C |
p. |
artikel |
26 |
Noninvasive acoustic time-of-flight measurements in heated, hermetically-sealed high explosives using a convolutional neural network
|
Greenhall, John |
|
|
9 |
C |
p. |
artikel |
27 |
On the application of clustering for extracting driving scenarios from vehicle data
|
Chetouane, Nour |
|
|
9 |
C |
p. |
artikel |
28 |
Origin of novel coronavirus causing COVID-19: A computational biology study using artificial intelligence
|
Nguyen, Thanh Thi |
|
|
9 |
C |
p. |
artikel |
29 |
Personality trait prediction by machine learning using physiological data and driving behavior
|
Evin, Morgane |
|
|
9 |
C |
p. |
artikel |
30 |
Predicting customer purpose of travel in a low-cost travel environment—A Machine Learning Approach
|
Samunderu, Eyden |
|
|
9 |
C |
p. |
artikel |
31 |
Predicting NEPSE index price using deep learning models
|
Pokhrel, Nawa Raj |
|
|
9 |
C |
p. |
artikel |
32 |
Predicting severely imbalanced data disk drive failures with machine learning models
|
Ahmed, Jishan |
|
|
9 |
C |
p. |
artikel |
33 |
Predicting stock market index using LSTM
|
Bhandari, Hum Nath |
|
|
9 |
C |
p. |
artikel |
34 |
Pre-trained transformers: an empirical comparison
|
Casola, Silvia |
|
|
9 |
C |
p. |
artikel |
35 |
Renewable energy management in smart grids by using big data analytics and machine learning
|
Mostafa, Noha |
|
|
9 |
C |
p. |
artikel |
36 |
Single-trial stimuli classification from detected P300 for augmented Brain–Computer Interface: A deep learning approach
|
Leoni, Jessica |
|
|
9 |
C |
p. |
artikel |
37 |
Solving the class imbalance problem using a counterfactual method for data augmentation
|
Temraz, Mohammed |
|
|
9 |
C |
p. |
artikel |
38 |
SpecRp: A spectral-based community embedding algorithm
|
Tautenhain, Camila P.S. |
|
|
9 |
C |
p. |
artikel |
39 |
Summarization of financial reports with TIBER
|
Vanetik, Natalia |
|
|
9 |
C |
p. |
artikel |
40 |
Time-to-event modeling for hospital length of stay prediction for COVID-19 patients
|
Wen, Yuxin |
|
|
9 |
C |
p. |
artikel |