51 citations · 51 across the 3 of their papers we have counts for
4 papers
FLIM-based Salient Object Detection Networks with Adaptive Decoders
Gilson Junior Soares, Matheus Abrantes Cerqueira, Jancarlo F. Gomes +3
Salient Object Detection (SOD) methods can locate objects that stand out in an image, assign higher values to their pixels in a saliency map, and binarize the map outputting a pred…
Multi-level Cellular Automata for FLIM networks
Felipe Crispim Salvagnini, Jancarlo F. Gomes, Cid A. N. Santos +2
The necessity of abundant annotated data and complex network architectures presents a significant challenge in deep-learning Salient Object Detection (deep SOD) and across the broa…
Flyweight FLIM Networks for Salient Object Detection in Biomedical Images
Leonardo M. Joao, Jancarlo F. Gomes, Silvio J. F. Guimaraes +2
Salient Object Detection (SOD) with deep learning often requires substantial computational resources and large annotated datasets, making it impractical for resource-constrained ap…
A comprehensive review and new taxonomy on superpixel segmentation
I. B. Barcelos, F. de C. Belém, L. de M. João +3
Superpixel segmentation consists of partitioning images into regions composed of similar and connected pixels. Its methods have been widely used in many computer vision application…