Degradation-resistant unfolding network for heterogeneous image fusion
Heterogeneous image fusion (HIF) techniques aim to enhance image quality by merging
complementary information from images captured by different sensors. Among these …
complementary information from images captured by different sensors. Among these …
Strategic preys make acute predators: Enhancing camouflaged object detectors by generating camouflaged objects
Camouflaged object detection (COD) is the challenging task of identifying camouflaged
objects visually blended into surroundings. Albeit achieving remarkable success, existing …
objects visually blended into surroundings. Albeit achieving remarkable success, existing …
Hqg-net: Unpaired medical image enhancement with high-quality guidance
Unpaired medical image enhancement (UMIE) aims to transform a low-quality (LQ) medical
image into a high-quality (HQ) one without relying on paired images for training. While most …
image into a high-quality (HQ) one without relying on paired images for training. While most …
Reti-diff: Illumination degradation image restoration with retinex-based latent diffusion model
Illumination degradation image restoration (IDIR) techniques aim to improve the visibility of
degraded images and mitigate the adverse effects of deteriorated illumination. Among these …
degraded images and mitigate the adverse effects of deteriorated illumination. Among these …
Ivf-net: An infrared and visible data fusion deep network for traffic object enhancement in intelligent transportation systems
Infrared and visible data fusion (IVF) aims to generate a fused output that simultaneously
highlights salient thermal radiation features and preserves texture information, which can not …
highlights salient thermal radiation features and preserves texture information, which can not …
Low-shot learning and class imbalance: a survey
P Billion Polak, JD Prusa, TM Khoshgoftaar - Journal of Big Data, 2024 - Springer
The tasks of few-shot, one-shot, and zero-shot learning—or collectively “low-shot
learning”(LSL)—at first glance are quite similar to the long-standing task of class imbalanced …
learning”(LSL)—at first glance are quite similar to the long-standing task of class imbalanced …
SeqNet: Sequential networks for one-shot traffic sign recognition with transfer learning
In traffic sign recognition tasks, recognition of road signs by observing synthetic reference
images is a human-like ability that can be performed by one-shot learning algorithms. One …
images is a human-like ability that can be performed by one-shot learning algorithms. One …
GAN-HA: A generative adversarial network with a novel heterogeneous dual-discriminator network and a new attention-based fusion strategy for infrared and visible …
G Lu, Z Fang, J Tian, H Huang, Y Xu, Z Han… - Infrared Physics & …, 2024 - Elsevier
Infrared and visible image fusion (IVIF) aims to preserve thermal radiation information from
infrared images while integrating texture details from visible images. Thermal radiation …
infrared images while integrating texture details from visible images. Thermal radiation …
Zero-Inflated Text Data Analysis using Generative Adversarial Networks and Statistical Modeling
S Jun - Computers, 2023 - mdpi.com
In big data analysis, various zero-inflated problems are occurring. In particular, the problem
of inflated zeros has a great influence on text big data analysis. In general, the preprocessed …
of inflated zeros has a great influence on text big data analysis. In general, the preprocessed …
Unpaired Self-supervised Learning for Industrial Cyber-Manufacturing Spectrum Blind Deconvolution
Cyber-Manufacturing combines industrial big data with intelligent analysis to find and
understand the intangible problems in decision-making, which requires a systematic method …
understand the intangible problems in decision-making, which requires a systematic method …