Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets and deep convolutional neural networks (CNNs). CNNs enable learning ...

Accurate image segmentation of skin lesions is crucial for the detection and treatment of skin cancer. Based on the modern state space model Mamba, a novel hybrid CNN-Mamba network (BEFNet) is ...

Detecting healthy arecanut leaves, yellow leaf disease in arecanut, and differentiating these from other types of leaves using deep learning involves designing an advanced neural network model for ...

CNNs (Convolutional Neural Networks) achieves considerable performance on the practically important text tasks (e.g. text classification). Nevertheless, neural network's accuracy significantly ...

Thus, we construct the deep learning model that extracts the spatial and temporal features from the heartbeat signal by CNN and LSTM. Based on the extracted features, the ECG signal is reconstructed.

In many of the iris biometric applications plays a major role in tracking the gaze, detecting fatigue, and predicting the age of a person, etc. that were built for human-computer interaction and ...

In this article, we develop an end-to-end wireless communication system using deep neural networks (DNNs), where DNNs are employed to perform several key functions, including encoding, decoding, ...

Human Activity Recognition (HAR) is vital across multiple applications, such as healthcare monitoring, smart home systems, and surveillance. Recently, Wi-Fi channel state information (CSI) has gained ...

The built year and structure of individual buildings are crucial factors for estimating and assessing potential earthquake and tsunami damage. Recent advances in sensing and analysis technologies ...

Glaucoma is a neurodegenerative disease that affects the optic nerve head and causes visual field defect. Current investigations focus on neural component which may overlook other important factors ...

Recently, deep learned enabled end-to-end communication systems have been developed to merge all physical layer blocks in the traditional communication systems, which make joint transceiver ...

Researchers evaluate Convolutional Neural Networks as tools for early identification and staging of Alzheimer's disease (AD) using MRI data collected from the Open Access Series of Imaging Studies ...