My Account | Careers | Downloads | Blog

ABSTRACT:

Images that have a different visual appearance may be semantically related using a higher level conceptualization. However, image classification and retrieval systems tend to rely only on the low-level visual structure within images. This paper presents a framework to deal with this semantic gap limitation by exploiting the well-known bag-of-visual words (BVW) to represent visual content. The novelty of this paper is threefold. First, the quality of visual words is improved by constructing visual words from representative keypoints. Second, domain specific “non-informative visual words” are detected which are useless to represent the content of visual data but which can degrade the categorization capability. Distinct from existing frameworks, two main characteristics for non-informative visual words are defined: a high document frequency (DF) and a small statistical association with all the concepts in the collection. The third contribution in this paper is that a novel method is used to restructure the vector space model of visual words with respect to a structural ontology model in order to resolve visual synonym and polysemy problems. The experimental results show that our method can disambiguate visual word senses effectively and can significantly improve classification, interpretation, and retrieval performance for the athletics images.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Reliability-Aware Multi-Objective Optimization-Based Routing Protocol for VANETs Using Enhanced Gaussian Mutation Harmony Searching ABSTRACT: Vehicular Ad Hoc Networks, or VANETs, are a relatively new form of
PROJECT TITLE : Real-Time Tracking Algorithm for Aerial Vehicles Using Improved Convolutional Neural Network and Transfer Learning ABSTRACT: A real-time tracking algorithm that makes use of an improved convolutional neural network
PROJECT TITLE : Using Randomness to Improve Robustness of Tree-based Models Against Evasion Attacks ABSTRACT: Applications in the field of security have seen widespread adoption of machine learning models. On the other hand, it
PROJECT TITLE : Enhanced Discrete Multi-modal Hashing More Constraints yet Less Time to Learn ABSTRACT: As a result of the meteoric rise in the amount of multimedia data, multi-modal hashing, a potentially useful method that could
PROJECT TITLE : Enhanced Wi-Fi RTT Ranging: A Sensor-Aided Learning Approach ABSTRACT: Through the utilization of round-trip time (RTT) measurements, the fine timing measurement (FTM) protocol was developed with the intention

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry