24 Result(s)
within
Conference Paper
Hai**g Guan
-
Chapter and Conference Paper
Reinforcement Learning-Based Algorithm for Real-Time Automated Parking Decision Making
Recently, automated parking has gained attention for its ability to enhance parking accuracy and provide a comfortable experience for car owners. However, with the increasing number of vehicles in the parking ...
-
Chapter and Conference Paper
Face Detection System Based on Deep Learning
The face is a special target. In order to obtain better detection results, researchers have improved and optimized the target detection algorithm, and proposed many excellent face detection algorithms. This pa...
-
Chapter and Conference Paper
Self-supervised Multi-object Tracking with Cycle-Consistency
Multi-object tracking is a challenging video task that requires both locating the objects in the frames and associating the objects among the frames, which usually utilizes the tracking-by-detection paradigm. ...
-
Chapter and Conference Paper
Face Detection of Innovation Base Based on Faster RCNN
In order to improve the efficiency of teachers’ attendance and save teachers’ energy and time, this paper proposes a face detection algorithm based on improved Faster-RCNN, in order to overcome the problems of...
-
Chapter and Conference Paper
Pervasive Monitoring of Gastrointestinal Health of Newborn Babies
Babies needing intensive care are at risk of develo** gastrointestinal problems, such as feed intolerance and necrotizing enterocolitis (NEC). Monitoring, early detection, and prevention of bowel diseases in...
-
Chapter and Conference Paper
An Integrated Deep Architecture for Lesion Detection in Breast MRI
Complex nature of medical images and tedious process of data exploration calls for the development of Computer Aided Detection (CADe) methods to ease the process of lesion detection. Recent deep learning-based...
-
Chapter and Conference Paper
Dual Adversarial Network for Deep Active Learning
Active learning, reducing the cost and workload of annotations, attracts increasing attentions from the community. Current active learning approaches commonly adopted uncertainty-based acquisition functions fo...
-
Chapter and Conference Paper
FTL: A Universal Framework for Training Low-Bit DNNs via Feature Transfer
Low-bit Deep Neural Networks (low-bit DNNs) have recently received significant attention for their high efficiency. However, low-bit DNNs are often difficult to optimize due to the saddle points in loss surfac...
-
Chapter and Conference Paper
Qualitative Instead of Quantitative: Towards Practical Data Analysis Under Differential Privacy
Differential privacy (DP) has become the de facto standard in the academic and industrial communities. Although DP can provide strong privacy guarantee, it also brings a major of performance loss for data mini...
-
Chapter and Conference Paper
Analysis of User’s Abnormal Behavior Based on Behavior Sequence in Enterprise Network
There are many abnormal user behavior in the enterprise network environment, how to monitor it effectively is a hot research hotspot. At present, the analysis of abnormal behavior is mainly through the means o...
-
Chapter and Conference Paper
Location Privacy Protected Recommendation System in Mobile Cloud
As the core of location-based services (LBS), the LBS-oriented recommendation systems, which suggest the points-of-interest (POIs) to users by analyzing the distribution of the user’s previous points-of-intere...
-
Chapter and Conference Paper
DaSS: Dynamic Time Slice Scheduler for Virtual Machine Monitor
I/O performance is an important factor in virtualization technology. However, the hypervisor and the scheduler brings impact on the I/O performance, since the scheduler considers I/O-intensive Virtual Machine ...
-
Chapter and Conference Paper
HYBit: A Hybrid Taint Analyzing Framework for Binary Programs
For the purpose of discovering security flaws in software, many dynamic and static taint analyzing techniques have been proposed. The dynamic techniques can precisely find the security flaws of the software; b...
-
Chapter and Conference Paper
A Improved Clustering Analysis Method Based on Fuzzy C-Means Algorithm by Adding PSO Algorithm
Fuzzy c-means algorithm (FCM) is one of the most widely used clustering methods for modern medical image segmentation applications. However the conventional FCM algorithm has certain possibilities of convergin...
-
Chapter and Conference Paper
Fuzzy C-means Clustering with Bilateral Filtering for Medical Image Segmentation
Fuzzy c-means (FCM) is a widely used unsupervised pattern recognition method for medical image segmentation. The conventional FCM algorithm and some existing variants are either sensitive to noise or prone to ...
-
Chapter and Conference Paper
Flexible Endian Adjustment for Cross Architecture Binary Translation
Different architectures and/or ISA (Instruction Set Architecture) representations hold different data arranging formats in the memory. Therefore, the adjustment of byte packing order (endianness) is indispensa...
-
Chapter and Conference Paper
Text Localization and Recognition in Complex Scenes Using Local Features
We describe an approach using local features to resolve problems in text localization and recognition in complex scenes. Low image quality, complex background and variations of text make these problems challen...
-
Chapter and Conference Paper
A Novel System for Robust Text Location and Recognition of Book Covers
Text location and recognition is a vital and fundamental problem of processing images. In this paper we propose a novel system for text location and recognition focused on book covers. Our work consists of two...
-
Chapter and Conference Paper
MTCrossBit: A Dynamic Binary Translation System Using Multithreaded Optimization Framework
Conventional optimization algorithms which are widely used in static compiler—including peephole, instruction selection, Graph coloring register allocation, and so on—cannot be effectively implemented in DBT (...
-
Chapter and Conference Paper
Ant Algorithm Applied in the Minimal Cost Maximum Flow Problem
The minimal cost maximum flow problem is a classical combinational optimization problem. Based on the characteristic of ant algorithm and the minimal cost maximum flow problem, a graph mode is presented to use...
