Ensemble learning: A survey
O Sagi, L Rokach - Wiley interdisciplinary reviews: data mining …, 2018 - Wiley Online Library
Ensemble methods are considered the state‐of‐the art solution for many machine learning
challenges. Such methods improve the predictive performance of a single model by training …
challenges. Such methods improve the predictive performance of a single model by training …
Facial sentiment analysis using AI techniques: state-of-the-art, taxonomies, and challenges
With the advancements in machine and deep learning algorithms, the envision of various
critical real-life applications in computer vision becomes possible. One of the applications is …
critical real-life applications in computer vision becomes possible. One of the applications is …
Facial emotion recognition using transfer learning in the deep CNN
Human facial emotion recognition (FER) has attracted the attention of the research
community for its promising applications. Mapping different facial expressions to the …
community for its promising applications. Mapping different facial expressions to the …
Deep convolutional neural networks with ensemble learning and transfer learning for capacity estimation of lithium-ion batteries
It is often difficult for a machine learning model trained based on a small size of
charge/discharge cycling data to produce satisfactory accuracy in the capacity estimation of …
charge/discharge cycling data to produce satisfactory accuracy in the capacity estimation of …
A star-nose-like tactile-olfactory bionic sensing array for robust object recognition in non-visual environments
M Liu, Y Zhang, J Wang, N Qin, H Yang, K Sun… - Nature …, 2022 - nature.com
Object recognition is among the basic survival skills of human beings and other animals. To
date, artificial intelligence (AI) assisted high-performance object recognition is primarily …
date, artificial intelligence (AI) assisted high-performance object recognition is primarily …
AdaBoost-CNN: An adaptive boosting algorithm for convolutional neural networks to classify multi-class imbalanced datasets using transfer learning
Ensemble models achieve high accuracy by combining a number of base estimators and
can increase the reliability of machine learning compared to a single estimator. Additionally …
can increase the reliability of machine learning compared to a single estimator. Additionally …
Local learning with deep and handcrafted features for facial expression recognition
We present an approach that combines automatic features learned by convolutional neural
networks (CNN) and handcrafted features computed by the bag-of-visual-words (BOVW) …
networks (CNN) and handcrafted features computed by the bag-of-visual-words (BOVW) …
Adversarial attacks on deep neural networks for time series classification
Time Series Classification (TSC) problems are encountered in many real life data mining
tasks ranging from medicine and security to human activity recognition and food safety. With …
tasks ranging from medicine and security to human activity recognition and food safety. With …
Ensemble of 3D densely connected convolutional network for diagnosis of mild cognitive impairment and Alzheimer's disease
Automatic diagnosis of Alzheimer's disease (AD) and mild cognition impairment (MCI) from
3D brain magnetic resonance (MR) images plays an important role in early treatment of …
3D brain magnetic resonance (MR) images plays an important role in early treatment of …
In search of a robust facial expressions recognition model: A large-scale visual cross-corpus study
Many researchers have been seeking robust emotion recognition system for already last two
decades. It would advance computer systems to a new level of interaction, providing much …
decades. It would advance computer systems to a new level of interaction, providing much …