Distinguishing counterfeit news is an essential undertaking in the contemporary era of digital technology. Fabricated news refers to information that has been deliberately fabricated or manipulated ...

The aim of the work is to design a secure and accurate Speech Emotion Recognition (SER) system using a RNN model to classify emotions from speech data. The system’s predictive accuracy is evaluated ...

Recent advancements in natural language processing have led to the development of highly efficient transformer-based models, yet Arabic handwritten text recognition remains challenging due to the ...

To address the significant scale differences between cracks and backgrounds and the loss of spatial detail in segmentation processes, which subsequently impacts segmentation accuracy, a dual-scale ...

As the Internet continues to evolve rapidly, the accuracy and efficiency of recommendation systems are crucial for Internet platforms. Concurrently, the continuous advancement of deep learning has led ...

To analyse the DeepFakes, which are AI-generated synthetic media that impersonate real people and pose substantial threats to digital content security, privacy, and authenticity. This research ...

This paper proposes a hybrid CNN-transformer network called HCTSpeckle, an encoder-decoder network with a fusion block designed to enhance ultrasound images. The fusion block combines swin ...

Motivated by the three-blade symmetrical structure of WTs, we propose a new symmetry-aware pitch feature encoder-decoder network named PitchNet. A group feature encoding strategy is first designed to ...

In this article, we propose 3D-SCUMamba, an innovative architecture strategically integrating State Space Modeling-Based deep learning (Mamba) within the bottleneck of the encoder-decoder structure to ...

In this paper, we present a method to solve cells overlap and close boundaries problem during blood cells images segmentation with deep learning techniques. The CNN encoder-decoder based models have ...

To solve these problems, we propose a multi-scale dual-domain low-light image enhancement network (MDENet). The network consists of an encoder-decoder structure, introducing a spatial-frequency ...