3 citations · 3 across the 2 of their papers we have counts for
4 papers
Improving Lightweight Weed Detection via Knowledge Distillation
Ahmet Oğuz Saltık, Max Voigt, Sourav Modak +2
Weed detection is a critical component of precision agriculture, facilitating targeted herbicide application and reducing environmental impact. However, deploying accurate object d…
Exploring Model Quantization in GenAI-based Image Inpainting and Detection of Arable Plants
Sourav Modak, Ahmet Oğuz Saltık, Anthony Stein
Deep learning-based weed control systems often suffer from limited training data diversity and constrained on-board computation, impacting their real-world performance. To overcome…
Comparative Analysis of YOLOv9, YOLOv10 and RT-DETR for Real-Time Weed Detection
Ahmet Oğuz Saltık, Alicia Allmendinger, Anthony Stein
This paper presents a comprehensive evaluation of state-of-the-art object detection models, including YOLOv9, YOLOv10, and RT-DETR, for the task of weed detection in smart-spraying…
Assessing the Capability of YOLO- and Transformer-based Object Detectors for Real-time Weed Detection
Alicia Allmendinger, Ahmet Oğuz Saltık, Gerassimos G. Peteinatos +2
Spot spraying represents an efficient and sustainable method for reducing the amount of pesticides, particularly herbicides, used in agricultural fields. To achieve this, it is of…