1 citations · 1 across the 3 of their papers we have counts for
4 papers
When Language Model Guides Vision: Grounding DINO for Cattle Muzzle Detection
Rabin Dulal, Lihong Zheng, Muhammad Ashad Kabir
Muzzle patterns are among the most effective biometric traits for cattle identification. Fast and accurate detection of the muzzle region as the region of interest is critical to a…
CCoMAML: Efficient Cattle Identification Using Cooperative Model-Agnostic Meta-Learning
Rabin Dulal, Lihong Zheng, Ashad Kabir
Cattle identification is critical for efficient livestock farming management, currently reliant on radio-frequency identification (RFID) ear tags. However, RFID-based systems are p…
MHAFF: Multi-Head Attention Feature Fusion of CNN and Transformer for Cattle Identification
Rabin Dulal, Lihong Zheng, Muhammad Ashad Kabir
Convolutional Neural Networks (CNNs) have drawn researchers' attention to identifying cattle using muzzle images. However, CNNs often fail to capture long-range dependencies within…
LEISA: A Scalable Microservice-based System for Efficient Livestock Data Sharing
Mahir Habib, Muhammad Ashad Kabir, Lihong Zheng
In the livestock sector, the fragmented data landscape across isolated systems presents a significant challenge, necessitating interoperability and integration. In this article, we…