activity
20192021
most citedL-CNN: A Lattice cross-fusion strategy for multistream convolutional neural networks

3 citations · 9 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2021

Turning old models fashion again: Recycling classical CNN networks using the Lattice Transformation

Ana Paula G. S. de Almeida, Flavio de Barros Vidal

In the early 1990s, the first signs of life of the CNN era were given: LeCun et al. proposed a CNN model trained by the backpropagation algorithm to classify low-resolution images…

cs.CV20213 cited

NemaNet: A convolutional neural network model for identification of nematodes soybean crop in brazil

Andre da Silva Abade, Lucas Faria Porto, Paulo Afonso Ferreira +1

Phytoparasitic nematodes (or phytonematodes) are causing severe damage to crops and generating large-scale economic losses worldwide. In soybean crops, annual losses are estimated…

cs.CV20203 cited

Plant Diseases recognition on images using Convolutional Neural Networks: A Systematic Review

Andre S. Abade, Paulo Afonso Ferreira, Flavio de Barros Vidal

Plant diseases are considered one of the main factors influencing food production and minimize losses in production, and it is essential that crop diseases have fast detection and…

cs.CV20203 cited

L-CNN: A Lattice cross-fusion strategy for multistream convolutional neural networks

Ana Paula G. S. de Almeida, Flavio de Barros Vidal

This paper proposes a fusion strategy for multistream convolutional networks, the Lattice Cross Fusion. This approach crosses signals from convolution layers performing mathematica…

cs.CV2019

Estimating sex and age for forensic applications using machine learning based on facial measurements from frontal cephalometric landmarks

Lucas F. Porto, Laise N. Correia Lima, Ademir Franco +3

Facial analysis permits many investigations some of the most important of which are craniofacial identification, facial recognition, and age and sex estimation. In forensics, photo…