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Building Flyweight FLIM-based CNNs with Adaptive Decoding for Object Detection
State-of-the-art (SOTA) object detection methods have succeeded in several applications at the price of relying on heavyweight neural networks, which makes them inefficient and inviable for many applications with computational resource constraints.
Iterative Saliency Enhancement using Superpixel Similarity
ISESS estimates seeds for superpixel delineation from a given saliency map and defines superpixel queries in the foreground and background.
ITSELF: Iterative Saliency Estimation fLexible Framework
We compare ITSELF to two state-of-the-art saliency estimators on five metrics and six datasets, four of which are composed of natural-images, and two of biomedical-images.
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