40 citations · 75 across the 7 of their papers we have counts for
9 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…
Co-Training with Active Contrastive Learning and Meta-Pseudo-Labeling on 2D Projections for Deep Semi-Supervised Learning
David Aparco-Cardenas, Jancarlo F. Gomes, Alexandre X. Falcão +1
A major challenge that prevents the training of DL models is the limited availability of accurately labeled data. This shortcoming is highlighted in areas where data annotation bec…
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…
Building Flyweight FLIM-based CNNs with Adaptive Decoding for Object Detection
Leonardo de Melo Joao, Azael de Melo e Sousa, Bianca Martins dos Santos +4
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 inv…
Convolutional Neural Network Simplification with Progressive Retraining
D. Osaku, J. F. Gomes, A. X. Falcão
Kernel pruning methods have been proposed to speed up, simplify, and improve explanation of convolutional neural network (CNN) models. However, the effectiveness of a simplified mo…
Automated Diagnosis of Intestinal Parasites: A new hybrid approach and its benefits
D. Osaku, C. F. Cuba, Celso T. N. Suzuki +2
Intestinal parasites are responsible for several diseases in human beings. In order to eliminate the error-prone visual analysis of optical microscopy slides, we have investigated…
Semi-supervised deep learning based on label propagation in a 2D embedded space
Barbara Caroline Benato, Jancarlo Ferreira Gomes, Alexandru Cristian Telea +1
While convolutional neural networks need large labeled sets for training images, expert human supervision of such datasets can be very laborious. Proposed solutions propagate label…
Semi-Automatic Data Annotation guided by Feature Space Projection
Barbara Caroline Benato, Jancarlo Ferreira Gomes, Alexandru Cristian Telea +1
Data annotation using visual inspection (supervision) of each training sample can be laborious. Interactive solutions alleviate this by helping experts propagate labels from a few…