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20172025
most citedA Systematic Review of Machine Learning Techniques for Cattle Identification: Datasets, Methods and Future Directions

103 citations · 196 across the 13 of their papers we have counts for

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cs.CV20231 cited

Machine Learning Techniques for Estimating Soil Moisture from Mobile Captured Images

Muhammad Riaz Hasib Hossain, Muhammad Ashad Kabir

Precise Soil Moisture (SM) assessment is essential in agriculture. By understanding the level of SM, we can improve yield irrigation scheduling which significantly impacts food pro…

cs.CV20222 cited

Automatic Cattle Identification using YOLOv5 and Mosaic Augmentation: A Comparative Analysis

Rabin Dulal, Lihong Zheng, Muhammad Ashad Kabir +4

You Only Look Once (YOLO) is a single-stage object detection model popular for real-time object detection, accuracy, and speed. This paper investigates the YOLOv5 model to identify…

cs.CV2022103 cited

A Systematic Review of Machine Learning Techniques for Cattle Identification: Datasets, Methods and Future Directions

Md Ekramul Hossain, Muhammad Ashad Kabir, Lihong Zheng +3

Increased biosecurity and food safety requirements may increase demand for efficient traceability and identification systems of livestock in the supply chain. The advanced technolo…

cs.CV2022

Understanding the Effect of Smartphone Cameras on Estimating Munsell Soil Colors from Imagery

Ricky Sinclair, Muhammad Ashad Kabir

The Munsell soil color chart (MSCC) is a in laboratories under controlled conditions. To support an appbased solution, this paper explores three research areas including: (i) ident…

cs.CV2021

A Survey of Machine Learning Techniques for Detecting and Diagnosing COVID-19 from Imaging

Aishwarza Panday, Muhammad Ashad Kabir, Nihad Karim Chowdhury

Due to the limited availability and high cost of the reverse transcription-polymerase chain reaction (RT-PCR) test, many studies have proposed machine learning techniques for detec…