Search Results for author:
Found 12 papers, 5 papers with code
Adaptive Multi-modal Fusion of Spatially Variant Kernel Refinement with Diffusion Model for Blind Image Super-Resolution
Harnessing the potential of leveraging this a priori knowledge in the context of image super-resolution presents a compelling avenue.
APISR: Anime Production Inspired Real-World Anime Super-Resolution
In addition, we identify two anime-specific challenges of distorted and faint hand-drawn lines and unwanted color artifacts.
LogFormer: A Pre-train and Tuning Pipeline for Log Anomaly Detection
Log anomaly detection is a key component in the field of artificial intelligence for IT operations (AIOps).
Identification of morphological fingerprint in perinatal brains using quasi-conformal mapping and contrastive learning
The morphological fingerprint in the brain is capable of identifying the uniqueness of an individual.
VCISR: Blind Single Image Super-Resolution with Video Compression Synthetic Data
In this work, we for the first time, present a video compression-based degradation model to synthesize low-resolution image data in the blind SISR task.
M2C: Towards Automatic Multimodal Manga Complement
In other words, the Multimodal Manga Complement (M2C) task has not been investigated, which aims to handle the aforementioned issues by providing a shared semantic space for vision and language understanding.
Network pharmacology on the mechanism of Yi Qi Tong Qiao Pill inhibiting allergic rhinitis
Network target analysis was performed to explore the potential mechanisms of YQTQP in the treatment of AR and the mechanisms were classified into different modules according to their biological functions.
A network-based biomarkers discovery of Cold/Hot ZHENG chronic gastritis and Cold/Hot herbs of formulae
And we collected 25 formulae (with traditional effects related to Cold/Hot ZHENG) for CG and corresponding 89 Cold/Hot herbs (including Warm/Cool herbs) to discover features and construct target networks of Cold/Hot herbs on the basis of network target and enrichment analysis.
A Benchmark for Studying Diabetic Retinopathy: Segmentation, Grading, and Transferability
This dataset has 1, 842 images with pixel-level DR-related lesion annotations, and 1, 000 images with image-level labels graded by six board-certified ophthalmologists with intra-rater consistency.
DR-GAN: Conditional Generative Adversarial Network for Fine-Grained Lesion Synthesis on Diabetic Retinopathy Images
In this paper, we propose a diabetic retinopathy generative adversarial network (DR-GAN) to synthesize high-resolution fundus images which can be manipulated with arbitrary grading and lesion information.
Evaluation of Retinal Image Quality Assessment Networks in Different Color-spaces
Retinal image quality assessment (RIQA) is essential for controlling the quality of retinal imaging and guaranteeing the reliability of diagnoses by ophthalmologists or automated analysis systems.
Learning and Generalizing Motion Primitives from Driving Data for Path-Tracking Applications
Therefore, the goal of this paper is to generate the prediction results of lateral commands with confidence regions according to the reference based on the learned motion primitives.
