joaopauloschuler

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Achievements

Achievements

joaopauloschuler/README.md

Dr. JP - GitHub Repositories

More about my work can be found at:

Publications

Optimizing the first layers of a convolutional neural network:

Color-aware two-branch DCNN for efficient plant disease classification.
Reliable Deep Learning Plant Leaf Disease Classification Based on Light-Chroma Separated Branches.

Optimizing deep layers of a convolutional neural network:

Grouped Pointwise Convolutions Reduce Parameters in Convolutional Neural Networks.
An Enhanced Scheme for Reducing the Complexity of Pointwise Convolutions in CNNs for Image Classification Based on Interleaved Grouped Filters without Divisibility Constraints.

Publicações em Português:

Doctoral Thesis

JP's doctoral thesis can be read here.

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neural-api neural-api Public

CAI NEURAL API - Pascal based deep learning neural network API optimized for AVX, AVX2 and AVX512 instruction sets plus OpenCL capable devices including AMD, Intel and NVIDIA.

Pascal 382 199
k-neural-api k-neural-api Public

K-CAI NEURAL API - Keras based neural network API that will allow you to create parameter-efficient, memory-efficient, flops-efficient multipath models with new layer types. There are plenty of exa…

Python 134 103
two-path-noise-lab-plant-disease two-path-noise-lab-plant-disease Public

Source code for the paper "Reliable Deep Learning Plant Leaf Disease Classification Based on Light-Chroma Separated Branches".

Jupyter Notebook 20 4
two-branch-plant-disease two-branch-plant-disease Public

Source code for the paper "Color-aware two-branch DCNN for efficient plant disease classification".

Jupyter Notebook 14 4
gpt-3-for-pascal gpt-3-for-pascal Public

Pascal coded GPT-3

Jupyter Notebook 12
kEffNetV1 kEffNetV1 Public

This repository contains the source code for the paper "Grouped Pointwise Convolutions Reduce Parameters in Convolutional Neural Networks".

Jupyter Notebook 7 2