Chest X-ray Images for Lung Disease Detection Using Deep Learning Techniques: A Comprehensive Survey
MAA Al-qaness, J Zhu, D AL-Alimi, A Dahou… - … Methods in Engineering, 2024 - Springer
In medical imaging, the last decade has witnessed a remarkable increase in the availability
and diversity of chest X-ray (CXR) datasets. Concurrently, there has been a significant …
and diversity of chest X-ray (CXR) datasets. Concurrently, there has been a significant …
Feature distillation interaction weighting network for lightweight image super-resolution
Convolutional neural networks based single-image superresolution (SISR) has made great
progress in recent years. However, it is difficult to apply these methods to real-world …
progress in recent years. However, it is difficult to apply these methods to real-world …
An efficient unfolding network with disentangled spatial-spectral representation for hyperspectral image super-resolution
Hyperspectral image super-resolution (HSI SR) is dramatically impacted by high spectral
dimensionality, insufficient spatial resolution, and limited availability of training samples …
dimensionality, insufficient spatial resolution, and limited availability of training samples …
Multi-scale feature selection network for lightweight image super-resolution
Recently, many super-resolution (SR) methods based on convolutional neural networks
(CNNs) have achieved superior performance by utilizing deep and heavy models, which …
(CNNs) have achieved superior performance by utilizing deep and heavy models, which …
Faster and better: a lightweight transformer network for remote sensing scene classification
Remote sensing (RS) scene classification has received considerable attention due to its
wide applications in the RS community. Many methods based on convolutional neural …
wide applications in the RS community. Many methods based on convolutional neural …
Automatic pavement texture recognition using lightweight few-shot learning
Texture is a crucial characteristic of roads, closely related to their performance. The
recognition of pavement texture is of great significance for road maintenance professionals …
recognition of pavement texture is of great significance for road maintenance professionals …
Fabnet: Frequency-aware binarized network for single image super-resolution
Remarkable achievements have been obtained with binary neural networks (BNN) in real-
time and energy-efficient single-image super-resolution (SISR) methods. However, existing …
time and energy-efficient single-image super-resolution (SISR) methods. However, existing …
Performance estimation for the memristor-based computing-in-memory implementation of extremely factorized network for real-time and low-power semantic …
Nowadays many semantic segmentation algorithms have achieved satisfactory accuracy on
von Neumann platforms (eg, GPU), but the speed and energy consumption have not meet …
von Neumann platforms (eg, GPU), but the speed and energy consumption have not meet …
Multi-level landmark-guided deep network for face super-resolution
C Zhuang, M Li, K Zhang, Z Li, J Lu - Neural Networks, 2022 - Elsevier
Recent years deep learning-based methods incorporating facial prior knowledge for face
super-resolution (FSR) are advancing and have gained impressive performance. However …
super-resolution (FSR) are advancing and have gained impressive performance. However …
Lightweight image de-snowing: A better trade-off between network capacity and performance
Z Chen, Y Sun, X Bi, J Yue - Neural Networks, 2023 - Elsevier
The single image de-snowing task is an essential topic in computer vision, as images
captured on snowy days degrade the performance of current vision-based intelligent …
captured on snowy days degrade the performance of current vision-based intelligent …