… image classification and pattern recognition tasks. This study aims to leverage deep learning
techniques, particularly convolutional neural networks (… system, ensemble methods have …

… , such as neural networks and recurrent neural networks, offer even … , such as image
recognition, natural language processing, and … against the defined objectives and make necessary …

… There are several methods of designing neural network ensembles, such as weighted average
linear … Design of effective neural network ensembles for image classification purposes. …

… :Objectives: With the development and popularization of deep learning theory, deep neural
networks are widely used in image … images, so it cannot effectively extract the detailed fea…

… effectiveness of hybrid comparison of multiple classification … to calculate the error, and uses
a recursive algorithm to correct … based on artificial neural network ensembles. Artificial Intelli…

… In this paper, an ensemble majority vote classifier to enhance … Expressed ensemble
techniques are effective for sentiment … them into the neural network-based architecture that uses a …

… At the same time, another purpose of this paper is to explore all … image classification, speech
recognition, natural language … By processing vast amounts of data, deep neural networks …

… proposed algorithm improves the ensemble model black-box … SAR image classification with
deeper convolutional neural … convolutional neural network models in SAR target recognition…