Search Results for author:
Found 7 papers, 2 papers with code
Early and Accurate Detection of Tomato Leaf Diseases Using TomFormer
TomFormer performed well on the KUTomaDATA, PlantDoc, and PlantVillage datasets, with mean average accuracy (mAP) scores of 87%, 81%, and 83%, respectively.
MuLA-GAN: Multi-Level Attention GAN for Enhanced Underwater Visibility
The underwater environment presents unique challenges, including color distortions, reduced contrast, and blurriness, hindering accurate analysis.
ADOD: Adaptive Domain-Aware Object Detection with Residual Attention for Underwater Environments
This research presents ADOD, a novel approach to address domain generalization in underwater object detection.
Autonomous Underwater Robotic System for Aquaculture Applications
This work aims to develop a robotic-based automatic net defect detection system for aquaculture net pens oriented to on- ROV processing and real-time detection of different aqua-net defects such as biofouling, vegetation, net holes, and plastic.
Evaluating Deep Learning Assisted Automated Aquaculture Net Pens Inspection Using ROV
In marine aquaculture, inspecting sea cages is an essential activity for managing both the facilities' environmental impact and the quality of the fish development process.
Vision-Based Autonomous Navigation for Unmanned Surface Vessel in Extreme Marine Conditions
To overcome these issues, this paper presents an autonomous vision-based navigation framework for tracking target objects in extreme marine conditions.
Tomato Maturity Recognition with Convolutional Transformers
In this paper, the authors propose a novel method for tomato maturity classification using a convolutional transformer.
