Deep learning for image colorization: Current and future prospects
Image colorization, as an essential problem in computer vision (CV), has attracted an
increasing amount of researchers attention in recent years, especially deep learning-based …
increasing amount of researchers attention in recent years, especially deep learning-based …
[HTML][HTML] Improved colorization and classification of intracranial tumor expanse in MRI images via hybrid scheme of Pix2Pix-cGANs and NASNet-large
M Mehmood, N Alshammari, SA Alanazi… - Journal of King Saud …, 2022 - Elsevier
Clinical image processing plays a significant role in healthcare systems and is a widely used
methodology of the current era. The Intracranial tumor affects children and adults as it is the …
methodology of the current era. The Intracranial tumor affects children and adults as it is the …
Generative adversarial learning in YUV color space for thin cloud removal on satellite imagery
X Wen, Z Pan, Y Hu, J Liu - Remote Sensing, 2021 - mdpi.com
Clouds are one of the most serious disturbances when using satellite imagery for ground
observations. The semi-translucent nature of thin clouds provides the possibility of 2D …
observations. The semi-translucent nature of thin clouds provides the possibility of 2D …
[PDF][PDF] An Improved Encoder-Decoder CNN with Region-Based Filtering for Vibrant Colorization.
Colorization is the practice of adding appropriate chromatic values to monochrome
photographs or videos. A real-valued luminance image can be mapped to a three …
photographs or videos. A real-valued luminance image can be mapped to a three …
A novel unbiased deep learning approach (dl-net) in feature space for converting gray to color image
Gray to Color conversion causes difficulties because of the nature of its intrinsic multi-
modality. Despite recent significant advancements in this domain by numerous learning …
modality. Despite recent significant advancements in this domain by numerous learning …
Siamese transformer network-based similarity metric learning for cross-source remote sensing image retrieval
As a fundamental technique for mining and analysis of remote sensing (RS) big data,
content-based remote sensing image retrieval (CBRSIR) has received a lot of attention …
content-based remote sensing image retrieval (CBRSIR) has received a lot of attention …
CCC: Color Classified Colorization
Automatic colorization of gray images with objects of different colors and sizes is challenging
due to inter-and intra-object color variation and the small area of the main objects due to …
due to inter-and intra-object color variation and the small area of the main objects due to …
Generation of the nir spectral band for satellite images with convolutional neural networks
The near-infrared (NIR) spectral range (from 780 to 2500 nm) of the multispectral remote
sensing imagery provides vital information for landcover classification, especially …
sensing imagery provides vital information for landcover classification, especially …
A fully-automatic image colorization scheme using improved CycleGAN with skip connections
Image colorization is the process of assigning different RGB values to each pixel of a given
grayscale image to obtain the corresponding colorized image. In this work, we propose a …
grayscale image to obtain the corresponding colorized image. In this work, we propose a …
MultiCut-MultiMix: a two-level data augmentation method for detecting small and densely distributed objects in large-size images
Z Xin, T Lu, Y Li, X You - The Visual Computer, 2024 - Springer
Detecting small and densely distributed (SDD) objects in large-size images is quite
challenging due to the facts that directly inputting such images to the detection network …
challenging due to the facts that directly inputting such images to the detection network …