An advanced deep learning models-based plant disease detection: A review of recent research
Plants play a crucial role in supplying food globally. Various environmental factors lead to
plant diseases which results in significant production losses. However, manual detection of …
plant diseases which results in significant production losses. However, manual detection of …
Transfer learning in environmental remote sensing
Abstract Machine learning (ML) has proven to be a powerful tool for utilizing the rapidly
increasing amounts of remote sensing data for environmental monitoring. Yet ML models …
increasing amounts of remote sensing data for environmental monitoring. Yet ML models …
Ccnet: Criss-cross attention for semantic segmentation
Full-image dependencies provide useful contextual information to benefit visual
understanding problems. In this work, we propose a Criss-Cross Network (CCNet) for …
understanding problems. In this work, we propose a Criss-Cross Network (CCNet) for …
A review of deep learning in multiscale agricultural sensing
Population growth, climate change, and the worldwide COVID-19 pandemic are imposing
increasing pressure on global agricultural production. The challenge of increasing crop yield …
increasing pressure on global agricultural production. The challenge of increasing crop yield …
AgriFusion: An architecture for IoT and emerging technologies based on a precision agriculture survey
Precision Agriculture (PA) is a management strategy that utilizes communication and
information technology for farm management. It is a key to improve productivity by using the …
information technology for farm management. It is a key to improve productivity by using the …
Pointflow: Flowing semantics through points for aerial image segmentation
Abstract Aerial Image Segmentation is a particular semantic segmentation problem and has
several challenging characteristics that general semantic segmentation does not have …
several challenging characteristics that general semantic segmentation does not have …
AgriSegNet: Deep aerial semantic segmentation framework for IoT-assisted precision agriculture
Aerial inspection of agricultural regions can provide crucial information to safeguard from
numerous obstacles to efficient farming. Farmland anomalies such as standing water, weed …
numerous obstacles to efficient farming. Farmland anomalies such as standing water, weed …
What a mess: Multi-domain evaluation of zero-shot semantic segmentation
While semantic segmentation has seen tremendous improvements in the past, there are still
significant labeling efforts necessary and the problem of limited generalization to classes …
significant labeling efforts necessary and the problem of limited generalization to classes …
On creating benchmark dataset for aerial image interpretation: Reviews, guidances, and million-aid
The past years have witnessed great progress on remote sensing (RS) image interpretation
and its wide applications. With RS images becoming more accessible than ever before …
and its wide applications. With RS images becoming more accessible than ever before …
[HTML][HTML] A review on object detection in unmanned aerial vehicle surveillance
A Ramachandran, AK Sangaiah - International Journal of Cognitive …, 2021 - Elsevier
Purpose Computer vision in drones has gained a lot of attention from artificial intelligence
researchers. Providing intelligence to drones will resolve many real-time problems …
researchers. Providing intelligence to drones will resolve many real-time problems …