to support myself for the next 3years as i research, learn and build.

A preview into my vision of the next gen computers. And what im building.

Introduction

Hello people, i am looking to crowdfund a total amount of $30k to support myself for the next 3 years, as I research, learn and build in my interest areas which revolves a lot around Artificial Intelligence among a few other things. One of my current final goals, is to…

Introducing TReX

My desk in Microsoft Research :)

The article describes a bit about how i got into research and how i started building TReX to help myself and all researchers out there.

July 2019, i got my offer letter from Microsoft Research to join them as a Research Intern. Couldn’t be more happier. Didn’t really know that…

An Adversarial Attack

Fig 1. Its not a fish, its a bird :) [Confidences shown are the values of logits and not passed through softmax]

Summary of the paper
DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks
by
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, Pascal Frossard
Link to the paper:
https://arxiv.org/pdf/1511.04599.pdf

Overview

Deep Neural Networks achieve state of the art performances in many tasks but fail miserably on slightly perturbed images, perturbed in a meaningful…

A paper summary

Fig 2. PVANET Entire Model Vizualization

A paper summary of the paper
PVANET: Deep but Lightweight Neural Networks for Real-time Object Detection
by Xinyu Zhou, Cong Yao, He Wen, Yuzhi Wang, Shuchang Zhou, Weiran He, and Jiajun Liang
Link to the paper:
https://arxiv.org/pdf/1608.08021.pdf

Overview

This paper presents our lightweight feature extraction network architecture for object detection, named…

A Paper Summary

Fig 1. A conversation between a semantic segmented guy and a toon

This is a paper summary of the paper:
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
by
Adam Paszke
Paper:
https://arxiv.org/abs/1606.02147

Overview

ENet (Efficient Neural Network) gives the ability to perform pixel-wise semantic segmentation in real-time. ENet is upto 18x faster, requires 75x less FLOPs, has 79x less parameters…

A Paper Summary

Fig 1. Toons Discussing about converting Kuzushiji-Kanji to Modern Kanji

This is a paper summary of the paper:
Deep Learning for Classical Japanese Literature
by
Tarin Clanuwat, Mikel Bober-Irizar, Asanobu Kitamoto, Alex Lamb, Kazuaki Yamamoto, and David Ha.
Paper:
https://arxiv.org/abs/1812.01718

Overview

The paper introduces 3 new benchmark datasets for Machine Learning, namely:
- Kuzushiji-MNIST A drop-in replacement for MNIST dataset…

[Fig. 1] Two toons discussing Neural Style Transfer at the beach.

This is a paper summary of the paper:
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
by Justin Johnson, Alexandre Alahi, Li Fei-Fei.
Paper:
https://arxiv.org/pdf/1603.08155.pdf

Overview

This paper proposes the use of perceptual loss functions for training feed-forward networks for image transformation tasks, instead of using per-pixel loss functions.

Per-pixel loss…

Arc

Machine Learning | Python

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