In our study, we introduce a novel hybrid ensemble model that synergistically combines
LSTM, BiLSTM, CNN, GRU, and GloVe embeddings for the classification of gene mutations …

Abstract Vision Transformers (ViTs) have emerged as a promising approach for visual
recognition tasks, revolutionizing the field by leveraging the power of transformer-based …

Recognizing Arabic script is challenging for many reasons: The Arabic language is cursive
and morphologically rich. There is a high similarity between Arabic letters. Moreover, Arabic …

In the rapidly evolving domain of machine learning, ensuring model generalizability remains
a quintessential challenge. Overfitting, where a model exhibits superior performance on …

This paper introduces a novel ensemble approach for question classification using state-of-
the-art models--Electra, GloVe, and LSTM. The proposed model is trained and evaluated on …

In this study, we present an in-depth comparison of five different deep learning approaches
for the classification of gene mutations based on a dataset provided by the Kaggle …

With the improvement of economic level, cultural and artistic pursuits have become the new
life style of people. For painting exhibition style appreciation, the study uses deep learning …

Image stability is very important in a time when digital image communication is essential to
many fields. Modern online dangers are often too complicated for old security methods to …

This study examines various machine learning models to predict customer responses in the
auto insurance industry. We focus on metrics like accuracy, precision, recall, and F1-score …

In our study, we introduce a novel hybrid ensemble model that synergistically combines
LSTM, BiLSTM, CNN, GRU, and GloVe embeddings for the classification of gene mutations …