3 citations · 3 across the 3 of their papers we have counts for
6 papers
A100: A Hybrid Vision Foundation Model for Agricultural Plant Image Analysis
Mayur Pratim Das, Ajai Dubey, Aksshay Mathew P +5
The use of accurate vision models for crop monitoring, disease diagnosis, and plant phenotyping in agriculture is hindered by the lack of expertly annotated data, especially in dev…
MCLC-NET: Multimodal Continual Learning for Leaf Counting
Ruchi Bhatt, Pratibha Kumari, Shreya Bansal +3
Leaf counting is an important task in plant phenotyping for monitoring plant growth and estimating crop yield. Most existing methods rely on RGB images, but their performance is of…
Characterizing Continual Learning Scenarios and Strategies for Audio Analysis
Ruchi Bhatt, Pratibha Kumari, Dwarikanath Mahapatra +2
Audio analysis is useful in many application scenarios. The state-of-the-art audio analysis approaches assume the data distribution at training and deployment time will be the same…
Concept Drift Challenge in Multimedia Anomaly Detection: A Case Study with Facial Datasets
Pratibha Kumari, Priyankar Choudhary, Pradeep K. Atrey +1
Anomaly detection in multimedia datasets is a widely studied area. Yet, the concept drift challenge in data has been ignored or poorly handled by the majority of the anomaly detect…
Multimedia Datasets for Anomaly Detection: A Review
Pratibha Kumari, Anterpreet Kaur Bedi, Mukesh Saini
Multimedia anomaly datasets play a crucial role in automated surveillance. They have a wide range of applications expanding from outlier objects/ situation detection to the detecti…
Anomaly Detection in Audio with Concept Drift using Adaptive Huffman Coding
Pratibha Kumari, Mukesh Saini
When detecting anomalies in audio, it can often be necessary to consider concept drift: the distribution of the data may drift over time because of dynamically changing environment…