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-approximate-computing-techniques-for-deep-neural-networks-

Approximate computing technique is very much useful for improving efficiency (approx double) and reducing energy consumption. We will be using different adders and multipliers for this purpose and comparing their energy consumption and accuracy. And we have implemented it on Field Programmable Gate Array (FPGA) and ZEDBoard.

3d-mnist-classification

3D Convolutional Neural Network for 3D MNIST Classification

3d-mnist-s4tf

3D MNIST Point Cloud Classifier using 3D ConvNet with Swift for TensorFlow

3dmnist

3D version of the MNIST database of handwritten digits

3dmnist-1

Generate 3D MNIST data

4tu-css

Material for a Computational Social Science (CSS) Workshop hosted by the four Dutch technical universities.

a-pytorch-tutorial-to-object-detection

SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object Detection

ac-fpn

Implement of paper 《Attention-guided Context Feature Pyramid Network for Object Detection》

accel-brain-code

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) that I have written in my website. Especially, Natural Language Processing, Statistical Machine Learning, and Deep Reinforcement Learning are main topics.

activation-visualization-histogram

Compare SELUs (scaled exponential linear units) with other activations on MNIST, CIFAR10, etc.

active-gbssl

This is a project of my paper related to active learning and graph based semi-supervised learning, which is published on ICME 2014. The project is written by matlab

active-learning

active-learning-1

Official Matlab demo for AIFT - CVPR 2017

active-learning-bayesian-convolutional-neural-networks

Active Learning on Image Data using Bayesian ConvNets

active-learning-in-big-data

在hadoop和spark两个框架下实现大数据的主动学习算法

active-manifold-learning-toolbox

A toolbox for different active manifold learning methods

active-self-paced-learning

active_learning

Active learning toolbox for MATLAB

active_learning_class

Code for class on Deep Active Learning and Annotation

activesemisuperviseddeeplearning

Comparing active learning, semi-supervised learning and combination of them on deep learning.

activesvm

This code is a implementation of paper "Learning on the Border: Active Learning in Imbalanced Data Classification"

adapted_deep_embeddings

Code associated with "Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning"

adelaidet

AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.

advanced-deep-learning-with-keras

Advanced Deep Learning with Keras, published by Packt

adversarial-attack-cyclegan-and-pix2pix

Generating Adversarial Images for Image-to-Image models in Pytorch

adversarial-continual-learning

Implementation for the paper "Adversarial Continual Learning" in PyTorch.

adversarial-domain-adaptation

TF2 implementation of a domain adversarial neural network

adversarial-domain_adaptation_paper_implementations

Collection of unsupervised adversarial domain adaptation models and their pre-trained checkpoints.

adversarial-feature-augmentation

Code for the paper "Adversarial Feature Augmentation for Unsupervised Domain Adaptation", CVPR 2018

adversarialanddimensionality

First-Order Adversarial Vulnerability of Neural Networks and Input Dimension