1 citations · 1 across the 4 of their papers we have counts for
5 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…
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…
LEI: Livestock Event Information Schema for Enabling Data Sharing
Mahir Habib, Muhammad Ashad Kabir, Lihong Zheng +1
Data-driven advances have resulted in significant improvements in dairy production. However, the meat industry has lagged behind in adopting data-driven approaches, underscoring th…
LEI2JSON: Schema-based Validation and Conversion of Livestock Event Information
Mahir Habib, Muhammad Ashad Kabir, Lihong Zheng
Livestock producers often need help in standardising (i.e., converting and validating) their livestock event data. This article introduces a novel solution, LEI2JSON (Livestock Eve…