23 citations · 49 across the 7 of their papers we have counts for
7 papers
FPCD: An Open Aerial VHR Dataset for Farm Pond Change Detection
Chintan Tundia, Rajiv Kumar, Om Damani +1
Change detection for aerial imagery involves locating and identifying changes associated with the areas of interest between co-registered bi-temporal or multi-temporal images of a…
The MIS Check-Dam Dataset for Object Detection and Instance Segmentation Tasks
Chintan Tundia, Rajiv Kumar, Om Damani +1
Deep learning has led to many recent advances in object detection and instance segmentation, among other computer vision tasks. These advancements have led to wide application of d…
Cost Optimization of Water Distribution Networks: Model Refinement Is Better Than Problem-Specific Solving Techniques
Saumya Goyal, Om Damani, Ashutosh Mahajan
Existing techniques for the cost optimization of water distribution networks either employ meta-heuristics, or try to develop problem-specific optimization techniques. Instead, we…
Effectiveness of Testing, Tracing, Social Distancing and Hygiene in Tackling Covid-19 in India: A System Dynamics Model
Jayendran Venkateswaran, Om Damani
We present a System Dynamics (SD) model of the Covid-19 pandemic spread in India. The detailed age-structured compartment-based model endogenously captures various disease transmis…
Building an IDE for the Calculational Derivation of Imperative Programs
Dipak L. Chaudhari, Om Damani
In this paper, we describe an IDE called CAPS (Calculational Assistant for Programming from Specifications) for the interactive, calculational derivation of imperative programs. In…
Improving Pointwise Mutual Information (PMI) by Incorporating Significant Co-occurrence
Om P. Damani
We design a new co-occurrence based word association measure by incorporating the concept of significant cooccurrence in the popular word association measure Pointwise Mutual Infor…
Lexical Co-occurrence, Statistical Significance, and Word Association
Dipak Chaudhari, Om P. Damani, Srivatsan Laxman
Lexical co-occurrence is an important cue for detecting word associations. We present a theoretical framework for discovering statistically significant lexical co-occurrences from…