Myself BLACK,doing my Engineering final year in PSP college.For my final year project i am working Medical image processing field.Now i want ideas regarding the article Non local means speckle filtering of ultrasound images using Bayesian framework.I have attached the abstract of the project.

Abstract”In image processing, restoration is expected to improve
the qualitative inspection of the image and the performance
of quantitative image analysis techniques. In this paper, an adaptation
of the nonlocal (NL)-means filter is propos ....etc

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ABSTRACT :
Heterogeneous types of gene expressions may provide a better insight into the biological role of gene interaction with the environment, disease development and drug effect at the molecular level. In this paper for both exploring and prediction
purposes a Time Lagged Recurrent Neural Network with trajectory learning is proposed for identifying and classifying the gene functional patterns from the heterogeneous nonlinear time series microarray experiments. The pr ....etc

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Bayesian Networks are becoming an increasingly important area for research and application in the entire field of Artificial Intelligence. This paper explores the nature and implications for Bayesian Networks beginning with an n overview and comparison of inferential statistics and Bayesâ„¢ theorem. The nature, relevance and applicability for Bayesian Network theories for advanced computability form the core of the current discussion.

A number of current applications using Bayesian networks are examined. The paper concludes with a brief ....etc

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Spam Junk Mail Filter ....etc

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Modeling Surprise
INTRODUCTION
Much of modern life depends on forecasts: where the next hurricane will make landfall, how the stock market will react to falling home prices, who will win the next primary. While existing computer models predict many things fairly accurately, surprises still crop up, and we probably can't eliminate them. But Eric Horvitz, head of the Adaptive Systems and Interaction group at Microsoft Research, thinks we can at least minimize them, using a technique called surprise modeling.
Surpr ....etc

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Bayesian Networks are becoming an increasingly important area for research and application in the entire field of Artificial Intelligence. This paper explores the nature and implications for Bayesian Networks beginning with an n overview and comparison of inferential statistics and Bayesâ„¢ theorem. The nature, relevance and applicability for Bayesian Network theories for advanced computability form the core of the current discussion.

A number of current applications using Bayesian networks are examined. The paper concludes with a brief ....etc

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ABSTRACT :
Heterogeneous types of gene expressions may provide a better insight into the biological role of gene interaction with the environment, disease development and drug effect at the molecular level. In this paper for both exploring and prediction
purposes a Time Lagged Recurrent Neural Network with trajectory learning is proposed for identifying and classifying the gene functional patterns from the heterogeneous nonlinear time series microarray experiments. The pr ....etc

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Can you able to send me the project details like abstract , base paper, existing system and proposed system ....etc

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Abstract—Security risk assessment and mitigation are two vital processes that need to be executed to maintain a productive IT infrastructure. On one hand, models such as attack graphs and attack trees have been proposed to assess the cause-consequence relationships between various network states, while on the other hand, different decision problems have been explored to identify the minimum-cost hardening measures. However, these risk models do not help reason about the causal dependencies between network states. Further, the optimization for ....etc

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Bayesian Networks are becoming an increasingly important area for research and application in the entire field of Artificial Intelligence. This paper explores the nature and implications for Bayesian Networks beginning with an n overview and comparison of inferential statistics and Bayesâ„¢ theorem. The nature, relevance and applicability for Bayesian Network theories for advanced computability form the core of the current discussion. A number of current applications using Bayesian networks are examined. The paper concludes with a brief des ....etc

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Bayesian Networks are becoming an increasingly important area for research and application in the entire field of Artificial Intelligence. This paper explores the nature and implications for Bayesian Networks beginning with an n overview and comparison of inferential statistics and Bayesâ„¢ theorem. The nature, relevance and applicability for Bayesian Network theories for advanced computability form the core of the current discussion. A number of current applications using Bayesian networks are examined. The paper concludes with a brief des ....etc

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1. Bayesian Data Mining “ finding interestingly large counts in massive tables.
2. Frequent pattern mining for kernel trace data
3. Data Squashing “ compressing large datasets to facilitate statistical analysis.
4. Capturing Best Practice for Microarray Gene Expression
5. Mining Coherent Gene Clusters from Three-Dimensional Microarray Data.
6. A Precise Blocking Method for Record Linkage.
7. Real-world Data is Dirty: Data Cleansing and The Merge/Purge Problem
8. FRIL: A Tool for Comparative Record Linkage
9. Detecting ....etc

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1. Graphbased Recommendation on Social Networks
2. Adaptive Multiagent System For Traffic Monitoring
3. Architectural Risk Analysis of Software Systems Based on Security Patterns
4. Providing Architectural Languages and Tools Interoperability through Model Transformation Technologies
5. SAMI: The SLA Management Instance
6. The CoQUOS Approach to Continuous Queries in Unstructured Overlays
7. Introduction to the DomainDriven Data Mining Special Section
8. Beyond Redundancies A MetricInvariant Method for Unsupervised Feature Selection
9. ....etc

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Airspace Encounter Model for Estimating Collision Risk
Seminar Report
Submitted in partial fulfillment of the
requirements for the award of M.Tech Degree in
Electrical Engineering
(Guidance & Navigational Control)
of the University of Kerala
Presented By
Ms Anumol A
st
1 Semester, M.Tech, Roll No:10GNC02
Guided by
Smt S. Sreeja
Le ....etc

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Sparse Bayesian Learning Of Filters For Efficient Image Expansion

– Image Processing- Dotnet

We propose a framework for expanding a given image using an interpolator that is trained in advance with training data, based on sparse Bayesian estimation for determining the optimal and compact support for efficient image expansion. Experiments on test data show that learned interpolators are compact yet superior to classical ones. ....etc

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Electronic Data Interchange

Introduction
Prosperity, and even survival, for small businesses depends as never before on the ability to respond with speed and certainty to the challenges and opportunities that are presented by competitors and customers. Electronic Commerce provides an opportunity to increase competitive edge and consolidate and enhance both business to business and business to consumer trading relationships.

In the current competitive & fast moving world of E-commerce & Electronic data transfer , com ....etc

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