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vpomponiu's Projects

all-conv-keras icon all-conv-keras

All Convolutional Network: (https://arxiv.org/abs/1412.6806#) implementation in Keras

aml-all-classifiers icon aml-all-classifiers

The Peter Moss Acute Myeloid/Lymphoblastic Leukemia classifiers are a collection of projects that use computer vision to classify Acute Myeloid/Lymphoblastic Leukemia in unseen images. The projects include classifiers made with Tensorflow, Caffe, FastAI, Intel Movidius (NCS & NCS2), OpenVino and Python/Java/C++/R classifiers.

b-soid icon b-soid

Behavioral segmentation of open field in DeepLabCut, or B-SOID ("B-side"), is a pipeline that pairs unsupervised pattern recognition with supervised classification to achieve fast predictions of behaviors that are not predefined by users.

baselines icon baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

bnn icon bnn

Bayesian Neural Network in PyTorch

bnn-pynq icon bnn-pynq

Quantized Neural Networks (QNNs) on PYNQ

caiman icon caiman

Computational toolbox for large scale Calcium Imaging Analysis, including movie handling, motion correction, source extraction, spike deconvolution and result visualization.

cancer_nn icon cancer_nn

Skin Lesion Analysis Towards Melanoma Detection

cleverhans icon cleverhans

An adversarial example library for constructing attacks, building defenses, and benchmarking both

cntk icon cntk

Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

cvat icon cvat

Powerful and efficient Computer Vision Annotation Tool (CVAT)

deepfocus icon deepfocus

DeepFocus: Learned Image Synthesis for Computational Displays

differentiable_volumetric_rendering icon differentiable_volumetric_rendering

This repository contains the code for the CVPR 2020 paper "Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision"

dlib icon dlib

A toolkit for making real world machine learning and data analysis applications in C++

doppelganger icon doppelganger

Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions, IMC 2020 (Best Paper Finalist)

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