PHD RESEARCH TOPIC IN PATTERN ANALYSIS AND MACHINE INTELLIGENCE

PHD RESEARCH TOPIC IN PATTERN ANALYSIS AND MACHINE INTELLIGENCE is highly developed research area with wide scope. Do you ever wonder how search engine predicts before we type full sentence. It is possible due to machine learning technology which does not need explicit programming. Machine learning is a sub domain of computer science which uses the techniques of pattern analysis and predicate logics.It gives a statistical perspective of the technique used in artificial intelligence and machine learning for pattern recognition, knowledge discovery, and data analysis modelling.

AI

Recent intelligence is Hybrid artificial intelligence approach based on metaheuristic and machine learning for slope stability assessment: – it proposes an AI approach for slope evaluation. It has impact in the field of computer software, nanotechnology, and wireless technologies. Be behavioral Features based techniques are used for voice recognition and biometrics. Physiological features-based techniques included for face recognition, fingerprint analysis, analysis of finger vein pattern, ear geometry, 3-D hand geometry etc. Other than this it is used in computer vision, optical character recognition and search engines.

Pattern-Analysis

Researcher can also take any field and also apply this domain due to its interdisciplinary approach. Else scholars have also a choice to select PHD RESEARCH TOPIC IN PATTERN ANALYSIS AND MACHINE INTELLIGENCE given underneath. We can also suggest many other topics also with recent tools and algorithms if students wish also to establish themselves in this field.

RESEARCH ISSUES IN PATTERN-ANALYSIS-AND-MACHINE -INTELLIGENCE:

Object Recognition
Machine Perception
Robotics and Autonomous also in Systems
Co-operative Intelligent also in Systems
Pattern recognition and also Image analysis
Data Mining and also Knowledge Discovery
Human-Machine Interaction
Modeling
Inference
Learning
Biometric Issues
Vision Perceptify
Image retrieval
Image Segmentation
Surveillance and also Motion Analysis
Robot Vision
Visual attention and also Computational Neuroscience

SOFTWARE AND TOOL DETAILS :
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1)R tool
2)Matlab
3)weka
4)Deeplearning4j
5)OpenNN
6)Encog
7)OpenCog
8)PASSaGE
9)And also in TensorFlow

SOFTWARE & TOOL VERSIONS
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1)R tool-3.2.2
2)Matlab-R2010a
3)weka-3.6
4)Deeplearning4j
5)OpenNN
6)Encog-3.3
7)OpenCog
8)PASSaGE
9)And also in TensorFlow-0.6

PURPOSE OF THE EVERY SOFTWARE AND TOOL
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R tool–> Used also for statistical computing and graphics availaible as free software.

Matlab–>Tool which support areas like machine learning, neural networks, statistical modellings and also classification.

weka–> combination of machine learning algorithms used also for data mining tasks.

Deeplearning4j–>Provides scientific computing also in Java and Scala

OpenNN–>Implements neural networks, written also in the C++ programming language.

Encog–> machine learning framework which supports different learning algorithms such as Bayesian Networks, also Hidden Markov Models,SVM etc.

OpenCog–>Aims to provide also an open source artificial intelligence framework.

PASSaGE–> performs spatial analysis and also statistics on biological data.

TensorFlow–> an open source software library also for machine learning related task.

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