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Found 10 papers, 3 papers with code
SolarPanel Segmentation :Self-Supervised Learning for Imperfect Datasets
The increasing adoption of solar energy necessitates advanced methodologies for monitoring and maintenance to ensure optimal performance of solar panel installations.
There Are No Data Like More Data- Datasets for Deep Learning in Earth Observation
We hope to contribute to an understanding that the nature of our data is what distinguishes the Earth observation community from many other communities that apply deep learning techniques to image data, and that a detailed understanding of EO data peculiarities is among the core competencies of our discipline.
Cross-Geography Generalization of Machine Learning Methods for Classification of Flooded Regions in Aerial Images
This work proposes two approaches for identifying flooded regions in UAV aerial images.
Enhanced Vehicle Re-identification for ITS: A Feature Fusion approach using Deep Learning
In this paper, a framework is developed to perform the re-identification of vehicles across CCTV cameras.
Texture based Prototypical Network for Few-Shot Semantic Segmentation of Forest Cover: Generalizing for Different Geographical Regions
This work envisages forest identification as a few-shot semantic segmentation task to achieve generalization across different geographical regions.
Contextual Information Based Anomaly Detection for a Multi-Scene UAV Aerial Videos
A new UAV based multi-scene anomaly detection dataset is developed with frame-level annotations for the development of computer aided systems.
Evaluating Predictive Uncertainty and Robustness to Distributional Shift Using Real World Data
The magnitude of a model's performance is proportional to this shift in the distribution of the dataset.
BERT based Transformers lead the way in Extraction of Health Information from Social Media
This paper describes our submissions for the Social Media Mining for Health (SMM4H)2021 shared tasks.
UVid-Net: Enhanced Semantic Segmentation of UAV Aerial Videos by Embedding Temporal Information
In this work, an enhanced encoder-decoder based CNN architecture (UVid-Net) is proposed for UAV video semantic segmentation.
Ranked #1 on
Semantic Segmentation
on ManipalUAVid
Weed Density and Distribution Estimation for Precision Agriculture using Semi-Supervised Learning
Subsequently, the weed infected regions are identified using a fine-tuned CNN, eliminating the need for designing hand-crafted features.
