34 Result(s)
within
Computer Science
Image Processing and Computer Vision
**ngli Li
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Article
Multi-style image generation based on semantic image
Image generation has always been one of the important research directions in the field of computer vision. It has rich applications in virtual reality, image design, and video synthesis. Our experiments proved...
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Article
An algorithm of nonnegative matrix factorization under structure constraints for image clustering
Nonnegative matrix factorization (NMF) is a crucial method for image clustering. However, NMF may obtain low accurate clustering results because the factorization results contain no data structure information....
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Chapter and Conference Paper
IoU-Enhanced Attention for End-to-End Task Specific Object Detection
Without densely tiled anchor boxes or grid points in the image, sparse R-CNN achieves promising results through a set of object queries and proposal boxes updated in the cascaded training manner. However, due ...
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Chapter and Conference Paper
Cross Attention Based Style Distribution for Controllable Person Image Synthesis
Controllable person image synthesis task enables a wide range of applications through explicit control over body pose and appearance. In this paper, we propose a cross attention based style distribution module...
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Chapter and Conference Paper
Blind Perceptual Quality Assessment for Single Image Motion Deblurring
Single image deblurring is a typical ill-posed problem. Although a lot of effective algorithms have been proposed, there is a lack of blind evaluation metrics for the perceptual quality of deblurred images. In...
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Chapter and Conference Paper
Automatic Detection of Obstructive Sleep Apnea Based on Multimodal Imaging System and Binary Code Alignment
There are many patients with obstructive sleep apnea syndrome, which has caused concern. When it occurs, the nasal airflow disappears, and the breathing action of the chest and abdomen still exists. Therefore,...
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Chapter and Conference Paper
Hidden Human Target Detection Model Inspired by Physiological Signals
The current object detection algorithms will give unsatisfactory performance on the task of detecting hidden human targets. Therefore, in the current work, we propose a physiological signals powered hidden hum...
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Chapter and Conference Paper
A Coherent Cooperative Learning Framework Based on Transfer Learning for Unsupervised Cross-Domain Classification
In the practical application of medical image analysis, due to the different data distributions of source domain and target domain and the lack of the labels of target domain, domain adaptation for unsupervise...
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Chapter and Conference Paper
Novel View Synthesis on Unpaired Data by Conditional Deformable Variational Auto-Encoder
Novel view synthesis often needs the paired data from both the source and target views. This paper proposes a view translation model under cVAE-GAN framework without requiring the paired data. We design a cond...
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Chapter and Conference Paper
Blind Quality Assessment Method to Evaluate Cloud Removal Performance of Aerial Image
People often use image-inpainting-based methods to remove cloud from aerial images, but it lacks a targeted quantitative evaluator to assess the removal result. In order to solve this issue to some extent, we ...
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Chapter and Conference Paper
PMIQD 2019: A Pathological Microscopic Image Quality Database with Nonexpert and Expert Scores
In medical diagnostic analysis, pathological microscopic image is often regarded as a gold standard, and hence the study of pathological microscopic image is of great necessity. High quality microscopic pathol...
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Chapter and Conference Paper
Preliminary Study on Visual Attention Maps of Experts and Nonexperts When Examining Pathological Microscopic Images
Pathological microscopic image is regarded as a gold standard for the diagnosis of disease, and eye tracking technology is considered as a very effective tool for medical education. It will be very interesting...
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Chapter and Conference Paper
FetusMap: Fetal Pose Estimation in 3D Ultrasound
The 3D ultrasound (US) entrance inspires a multitude of automated prenatal examinations. However, studies about the structuralized description of the whole fetus in 3D US are still rare. In this paper, we prop...
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Chapter and Conference Paper
Age Estimation via Pose-Invariant 3D Face Alignment Feature in 3 Streams of CNN
This paper proposes an algorithm for age estimation intentionally considering the pose variation and local deformation of faces. Pose-invariant patches are extracted in face region, and they are located from t...
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Chapter and Conference Paper
Person Re-id by Incorporating PCA Loss in CNN
This paper proposes an algorithm, particularly a loss function and its end to end learning manner, for person re-identification task. The main idea is to take full advantage of the labels in a batch during tra...
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Chapter and Conference Paper
Generalizing Deep Models for Ultrasound Image Segmentation
Deep models are subject to performance drop when encountering appearance discrepancy, even on congeneric corpus in which objects share the similar structure but only differ slightly in appearance. This perform...
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Chapter and Conference Paper
Automatic and Efficient Standard Plane Recognition in Fetal Ultrasound Images via Multi-scale Dense Networks
The determination and interpretation of fetal standard planes (FSPs) in ultrasound examinations are the precondition and essential step for prenatal ultrasonography diagnosis. However, identifying multiple sta...
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Chapter and Conference Paper
Auto-tuning Neural Network Quantization Framework for Collaborative Inference Between the Cloud and Edge
Recently, deep neural networks (DNNs) have been widely applied in mobile intelligent applications. The inference for the DNNs is usually performed in the cloud. However, it leads to a large overhead of transmi...
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Chapter and Conference Paper
Quality Assessment of Fetal Head Ultrasound Images Based on Faster R-CNN
Clinically, the transthalamic plane of the fetal head is manually examined by sonographers to identify whether it is a standard plane. This examination routine is subjective, time-consuming and requires compre...
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Chapter and Conference Paper
Fast CNN Pruning via Redundancy-Aware Training
The heavy storage and computational overheads have become a hindrance to the deployment of modern Convolutional Neural Networks (CNNs). To overcome this drawback, many works have been proposed to exploit redun...
