50 Result(s)
within
**nli Liu
Artificial Intelligence
-
Article
Deep Learning-Based Image and Video Inpainting: A Survey
Image and video inpainting is a classic problem in computer vision and computer graphics, aiming to fill in the plausible and realistic content in the missing areas of images and videos. With the advance of de...
-
Article
A state-of-the-art survey of U-Net in microscopic image analysis: from simple usage to structure mortification
Microscopic image analysis technology helps solve the inadvertences of artificial traditional methods in disease, wastewater treatment, and environmental change monitoring analysis. Convolutional neural networ...
-
Chapter and Conference Paper
MS TextSpotter: An Intelligent Instance Segmentation Scheme for Semantic Scene Text Recognition in Asian Social Networks
Text detection and recognition in natural scenes is an im- important task in computer vision. However, most of the texts in natural scenes are curved, and the text background is complex and diverse. In recent ...
-
Article
RETRACTED ARTICLE: Cognitive computing for intelligent robots in assisting preschool children
-
Article
B2IPTS: A blockchain-based intellectual property transaction framework
In the era of the digital economy, the protection of digital intellectual property is an important issue. At present, blockchain is widely used in the field of intellectual property protection. The market cap ...
-
Chapter and Conference Paper
An Enhanced Model Based on Recurrent Convolutional Neural Network for Predicting the Stage of Chronic Obstructive Pulmonary Diseases
Chronic Obstructive Pulmonary Disease (COPD) is the third leading cause of death in China and has caused serious affect to health and life quality. However, the disease stage of COPD patient is difficult to be...
-
Chapter and Conference Paper
PBCI-DS: A Benchmark Peripheral Blood Cell Image Dataset for Object Detection
Blood testing has always been one of the important methods for disease diagnosis, but currently, blood testing instruments face the problems of long time consumption, complex processes, and limited detection t...
-
Chapter and Conference Paper
LFD-CD: Peripheral Blood Cells Detection Using a Lightweight Cell Detection Model with Full-Connection and Dropconnect
Blood testing is an important basis for the diagnosis of many diseases. However, the accuracy of detection instruments in hospitals is often not high, and manual detection of blood samples is sometimes necessa...
-
Chapter and Conference Paper
A Joint Learning Model for Open Set Recognition with Post-processing
In open set recognition (OSR), the model not only needs to correctly recognize known class samples, but also needs to be able to effectively reject unknown samples. To address this problem, we propose a joint ...
-
Chapter and Conference Paper
Novel TD-based Adaptive Control for Nonlinearly Parameterized Stochastic Systems
In this article, the adaptive tracking control of nonlinearly parameterized stochastic systems is developed via the nonlinear tracking differentiator technique. First, the Barrier Lyapunov function (BLF) is br...
-
Article
Modeling visual aesthetic perception: bridges between computed texture features and perceived beauty qualities in semantic experiments
The exploration of the potential relationship between computable low-level texture, such as features extracted from color and texture, and the perceived high-level aesthetic properties, such as warm or cold, s...
-
Chapter and Conference Paper
An Effective Data Balancing Strategy Based on Swarm Intelligence Algorithm for Malicious Code Detection and Classification
Data balance has a great impact on the performance of neural network training model, and the model trained with high-quality data is often more robust. In the task of malicious code detection and classificatio...
-
Article
Pyramid-dilated deep convolutional neural network for crowd counting
Statistics on crowds in crowded scenes can reflect the density level of crowds and provide safety warnings. This is a laborious task if conducted manually. In recent years, automated crowd counting has receive...
-
Chapter and Conference Paper
SMOF: Squeezing More Out of Filters Yields Hardware-Friendly CNN Pruning
Researchers have proposed various structured Convolutional Neural Networks (CNNs) pruning strategies to make them work efficiently on edge devices. However, most of them focus on reducing the number of filter ...
-
Article
Incremental Bayesian broad learning system and its industrial application
Broad learning system (BLS) is viewed as a class of neural networks with a broad structure, which exhibits an efficient training process through incremental learning. An incremental Bayesian framework broad le...
-
Chapter and Conference Paper
Hybrid Domain Convolutional Neural Network for Memory Efficient Training
For many popular Convolutional Neural Networks (CNNs), memory has become one of the major constraints for their efficient training and inference on edge devices. Recently, it is shown that the bottleneck lies ...
-
Chapter and Conference Paper
Research on Off-Path Exploits of Network Protocols
With the rapid development of the Internet industry, from a global perspective, the risks brought by network security are becoming increasingly prominent, and continue to penetrate into political, economic, cu...
-
Chapter and Conference Paper
Analysis of Influencing Factors and Countermeasures of Computer Network Security
Since the new century, with the gradual popularization of computer networks around the world, network security defense methods have become more sophisticated and comprehensive, but they are still unable to def...
-
Article
Background subtraction with Kronecker-basis-representation based tensor sparsity and \(l_{1,1,2}\) norm
Background subtraction is an important and fundamental step in video analysis and is a challenging task due to the dynamic background, bad weather, complex moving behaviors and huge amount of data in real-life...
-
Chapter and Conference Paper
Intelligent Power Controller of Wireless Body Area Networks Based on Deep Reinforcement Learning
Wireless Body Area networks allow groups of tiny sensors to communicate for purpose of medical applications. With the progress of sensor manufacture and artificial intelligence, abundant wearing devices are pr...
