2D-CNN Architecture for Accurate Classification of COVID-19 Related Pneumonia on X-Ray Images
PulseAugur coverage of 2D-CNN Architecture for Accurate Classification of COVID-19 Related Pneumonia on X-Ray Images — every cluster mentioning 2D-CNN Architecture for Accurate Classification of COVID-19 Related Pneumonia on X-Ray Images across labs, papers, and developer communities, ranked by signal.
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CNN EEG analysis shows frontal regions better predict hypnosis
Researchers have developed a 2D Convolutional Neural Network (CNN) to classify hypnotic susceptibility using EEG signals. While initial tests showed high accuracy in regions like the occipital lobe, a subject-independen…
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Hyperspectral image classification vulnerable to data leakage via spatial overlap
A new research paper highlights a critical issue in hyperspectral image classification: data leakage caused by spatial overlap in patch-based sampling. When training and testing data are drawn from the same image withou…
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New HMD Framework Offers Efficient Hyperspectral Image Classification
Researchers have developed a new framework called Holistic Multivariance Decomposition (HMD) for hyperspectral image classification. This novel approach aims to improve accuracy and efficiency by capturing complex spati…
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New hybrid deep learning model enhances RF modulation recognition
Researchers have developed a novel uncertainty-driven hybrid deep learning architecture for radio frequency (RF) modulation recognition. This system combines spectral information from FFT preprocessing with time-frequen…
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New framework enhances iris recognition with occlusion identification and reconstruction
Researchers have developed a new framework for iris recognition that aims to improve accuracy even when parts of the iris are obscured. The system first identifies the type of occlusion, such as eyelids or eyelashes, us…