activity
20192022
most citedA Survey on Machine Learning Techniques for Auto Labeling of Video, Audio, and Text Data

27 citations · 56 across the 10 of their papers we have counts for

collaborators

10 papers

cs.DB2022★ 1 cited

Experimental Analysis of Machine Learning Techniques for Finding Search Radius in Locality Sensitive Hashing

Omid Jafari, Parth Nagarkar

Finding similar data in high-dimensional spaces is one of the important tasks in multimedia applications. Approaches introduced to find exact searching techniques often use tree-ba…

cs.LG2021★ 27 cited

A Survey on Machine Learning Techniques for Auto Labeling of Video, Audio, and Text Data

Shikun Zhang, Omid Jafari, Parth Nagarkar

Machine learning has been utilized to perform tasks in many different domains such as classification, object detection, image segmentation and natural language analysis. Data label…

cs.CV2021

A Survey of Performance Optimization in Neural Network-Based Video Analytics Systems

Nada Ibrahim, Preeti Maurya, Omid Jafari +1

Video analytics systems perform automatic events, movements, and actions recognition in a video and make it possible to execute queries on the video. As a result of a large number…

cs.DB2021★ 8 cited

A Survey on Locality Sensitive Hashing Algorithms and their Applications

Omid Jafari, Preeti Maurya, Parth Nagarkar +2

Finding nearest neighbors in high-dimensional spaces is a fundamental operation in many diverse application domains. Locality Sensitive Hashing (LSH) is one of the most popular tec…

cs.DB2020★ 6 cited

Experimental Analysis of Locality Sensitive Hashing Techniques for High-Dimensional Approximate Nearest Neighbor Searches

Omid Jafari, Parth Nagarkar

Finding nearest neighbors in high-dimensional spaces is a fundamental operation in many multimedia retrieval applications. Exact tree-based indexing approaches are known to suffer…

cs.DB2020★ 8 cited

Improving Locality Sensitive Hashing by Efficiently Finding Projected Nearest Neighbors

Omid Jafari, Parth Nagarkar, Jonathan Montaño

Similarity search in high-dimensional spaces is an important task for many multimedia applications. Due to the notorious curse of dimensionality, approximate nearest neighbor techn…

cs.DB2020★ 3 cited

mmLSH: A Practical and Efficient Technique for Processing Approximate Nearest Neighbor Queries on Multimedia Data

Omid Jafari, Parth Nagarkar, Jonathan Montaño

Many large multimedia applications require efficient processing of nearest neighbor queries. Often, multimedia data are represented as a collection of important high-dimensional fe…

cs.MM2019

Efficient Bitmap-based Indexing and Retrieval of Similarity Search Image Queries

Omid Jafari, Parth Nagarkar, Jonathan Montaño

Finding similar images is a necessary operation in many multimedia applications. Images are often represented and stored as a set of high-dimensional features, which are extracted…

cs.DB2019

Drawbacks and Proposed Solutions for Real-time Processing on Existing State-of-the-art Locality Sensitive Hashing Techniques

Omid Jafari, Khandker Mushfiqul Islam, Parth Nagarkar

Nearest-neighbor query processing is a fundamental operation for many image retrieval applications. Often, images are stored and represented by high-dimensional vectors that are ge…

cs.DB2019★ 3 cited

qwLSH: Cache-conscious Indexing for Processing Similarity Search Query Workloads in High-Dimensional Spaces

Omid Jafari, John Ossorgin, Parth Nagarkar

Similarity search queries in high-dimensional spaces are an important type of queries in many domains such as image processing, machine learning, etc. Since exact similarity search…