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05/04/2023
MTLSegFormer: Multi-task Learning with Transformers for Semantic Segmentation in Precision Agriculture
Multi-task learning has proven to be effective in improving the performa...
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12/01/2022
GMM-IL: Image Classification using Incrementally Learnt, Independent Probabilistic Models for Small Sample Sizes
Current deep learning classifiers, carry out supervised learning and sto...
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05/21/2022
Facing the Void: Overcoming Missing Data in Multi-View Imagery
In some scenarios, a single input image may not be enough to allow the o...
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08/03/2020
AiRound and CV-BrCT: Novel Multi-View Datasets for Scene Classification
It is undeniable that aerial/satellite images can provide useful informa...
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06/25/2020
Fully Convolutional Open Set Segmentation
In semantic segmentation knowing about all existing classes is essential...
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01/27/2020
Towards Open-Set Semantic Segmentation of Aerial Images
Classical and more recently deep computer vision methods are optimized f...
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06/04/2019
An Introduction to Deep Morphological Networks
The recent impressive results of deep learning-based methods on computer...
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03/02/2019
Spatio-Temporal Vegetation Pixel Classification By Using Convolutional Networks
Plant phenology studies rely on long-term monitoring of life cycles of p...
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04/11/2018
Dynamic Multi-Scale Semantic Segmentation based on Dilated Convolutional Networks
Semantic segmentation requires methods capable of learning high-level fe...
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11/09/2017
Exploiting ConvNet Diversity for Flooding Identification
Flooding is the world's most costly type of natural disaster in terms of...
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02/04/2016