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Found 5 papers, 4 papers with code
SPOT: Self-Training with Patch-Order Permutation for Object-Centric Learning with Autoregressive Transformers
Unsupervised object-centric learning aims to decompose scenes into interpretable object entities, termed slots.
Keep It SimPool: Who Said Supervised Transformers Suffer from Attention Deficit?
By discussing the properties of each group of methods, we derive SimPool, a simple attention-based pooling mechanism as a replacement of the default one for both convolutional and transformer encoders.
What to Hide from Your Students: Attention-Guided Masked Image Modeling
In this work, we argue that image token masking differs from token masking in text, due to the amount and correlation of tokens in an image.
MARIDA: A benchmark for Marine Debris detection from Sentinel-2 remote sensing data
Currently, a significant amount of research is focused on detecting Marine Debris and assessing its spectral behaviour via remote sensing, ultimately aiming at new operational monitoring solutions.
Ranked #2 on
Image Segmentation
on MARIDA
Evaluating explainable artificial intelligence methods for multi-label deep learning classification tasks in remote sensing
Although deep neural networks hold the state-of-the-art in several remote sensing tasks, their black-box operation hinders the understanding of their decisions, concealing any bias and other shortcomings in datasets and model performance.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
+1
