38786909
Neural Network-Generated Image Retrieval and Refinement
The motivation for this work is to develop an image retrieval system that can discriminate between images and that can learn user’s preference with feedback to make more intelligent. This paper proposes a neural network to extend prototype refinement which retains information fed by users. The proposed three-layered neural network indexes an image database and makes clusters by an unsupervised approach at a hidden layer. Given a query, the neural system retrieves similar images by computing similarities with images in the near clusters by a supervised approach at an output layer. To provide preference, users can select some images as relevant ones or irrelevant ones. With this feedback, the proposed refinement method estimates global approximations of radial-basis functions centered, and simultaneously adjusts corresponding prototypes. The system demonstrated the effectiveness of prototype refinement generated by the proposed neural network.
34164098
A New EM Algorithm for Resource Allocation Network
Clustering usually assumes that the number of clusters is known or given. No knowledge of such a priori information is needed to find an appropriate number of clusters. This paper introduces an elliptical clustering algorithm with incremental growth of clusters, which is derived from the batch EM algorithm with a decay factor and a novelty criterion. The proposed algorithm can start with no or a small number of clusters. Whenever unusual data is presented, the algorithm adds a new cluster and finally the number of clusters in the data is obtained after clustering. The usefulness of the proposed algorithm is demonstrated for texture image segmentation and skin image segmentation.
30255791
Adaptive Model-Based Multi-person Tracking
This paper proposes a method for tracking and identifying persons from video image frames taken by a fixed camera. The majority of conventional video tracking surveillance systems assumes a likeness to a person's appearance for some time, and existing human tracking systems usually consider short-term situations. To address this situation, we use an adaptive background and human body model updated statistically frame-by-frame to correctly construct a person with body parts. The formed person is labeled and recorded in a person's list, which stores the individual's human body model details. Such recorded information can be used to identify tracked persons. The results of this experiment are demonstrated in several indoor situations.
24310355
Component-Based Online Learning for Face Detection and Verification
Component detectors can accurately locate facial components, and component-based approaches can be used to build detectors that can handle partial occlusions. This paper proposes a face detection and verification method using component-based online learning. The main difference from previously reported component-based approaches is the use of online learning, which is ideal for highly repetitive tasks. This results in faster and more accurate face detection, because system performance improves with continued use. Further, uncertainty is added by calculating the standard deviation of face components and their relations.
321298
NETKIT: a software component-based approach to programmable networking
While there has already been significant research in support of openness and programmability in networks, this paper argues that there remains a need for generic support for the integrated development, deployment and management of programmable networking software. We further argue that this support should explicitly address the management of run-time reconfiguration of systems, and should be independent of any particular programming paradigm (e.g. active networking or open signaling), programming language, or hardware/ operating system platform. In line with these aims, we outline an approach to the structuring of programmable networking software in terms of a ubiquitously applied software component model that can accommodate all levels of a programmable networking system from low-level system support, to in-band packet handling, to active networking execution environments to signaling and coordination.
6972987
Scalable service differentiation in a shared storage cache
Motivated by the need to enable easier data sharing and curb rising storage management costs, storage systems are becoming increasingly consolidated and thereby shared by a large number of users and applications. In such environments, service differentiation becomes increasingly important. Since caching is a fundamental and pervasive technique employed to improve the performance of storage systems, providing differentiated services from a storage cache is a crucial component of the entire end-to-end QoS solution. In this paper we discuss a QoS architecture for a shared storage proxy cache which can provide long-term hit rate assurances to competing classes. The proposed architecture consists of three components: (a) per-class feedback controllers that track the performance of each class, (b) a fairness controller that allocates excess resources fairly in the case when all goals are met, and (c) a contention resolver that decides cache allocation in the case when at least one class does not meet its target hit rate. We compare the performance of various feedback per-class controllers, and provide guidelines for designing QoS mechanisms for such a dynamic environment.
17067182
A dependable online testing and upgrade architecture for real-time embedded systems
When real-time embedded system software needs to be upgraded, it will be more dependable if the new software is sufficiently tested on the actual deployment platform. The challenge is to provide a safeguard for protecting the normal operations from faulty upgrades. However, the safeguard must be not only efficient but also able to be added and taken away as needed without shutting down the normal operations. We have developed an architecture based on simplex architecture and process resurrection and have applied it to the inverted pendulum control system. The measurements show that the overhead is small and justifiable.
42709388
Precomputing avatar behavior from human motion data
9830894
Odysseus: a High-Performance ORDBMS Tightly-Coupled with Spatial Database Features
We have earlier proposed the tight-coupling architecture for adding new data types into the DBMS engine. In this paper, we introduce the Odysseus ORDBMS and present its tightly-coupled spatial database features. We demonstrate a geographical information system (GIS) implemented using Odysseus.