Abstract: Dementia, a neurodegenerative disorder, requires early prediction and effective diagnosis for providing better treatment to avert the loss. The detection and classification of disease is ...
This work explores an efficient convolutional acceleration framework tailored for edge devices by integrating Depthwise Convolution with the Winograd algorithm. Through RTL-based hardware ...
High school sophomore Abigail Merchant has made it her mission to use technology to reduce flood-related deaths. The ...
Abstract: In the petroleum industry, light-quantum flowmeters can perform multiphase measurement of gas, liquid, and solid phases, which has attracted significant attention. However, their measurement ...
Abstract: Early and precise detection of plant diseases is crucial for enhancing crop yield and minimizing agricultural losses. This paper evaluates the performance of deep learning-based ...
Abstract: This paper proposes a novel hybrid classification model obtained by fusion of two Swarm Intelligence techniques (Bat Algorithms (BA) and Grey Wolf Optimizer (GWO)) with a Deep Convolutional ...
Abstract: Heart disease remains one of the leading causes of death worldwide. Effective management and prevention heavily depend on early detection and accurate prediction. However, traditional ...
Abstract: Orthogonal Frequency Division Multiplexing (OFDM) enables high-rate data transmission wards wirelss broadband connections. Accurate channel estimation continues to be an unsolved issue in ...
Abstract: Plant diseases have important consequences for livelihoods and economies, both on local and global scales, whereby the spread of plant pathogens can lead to high levels of damage to ...
Abstract: During the manufacturing, transportation, and assembly processes of Gas Insulated Switchgear (GIS), internal insulation defects can lead to partial discharge (PD), posing risks to ...
Abstract: Emotion intensity recognition is important for understanding mental states and improving human-computer interaction. Recently, electroencephalogram (EEG)-based spectrogram analysis was ...