Saurabh Singh | DeepAI

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∙ 09/12/2023

ssVERDICT: Self-Supervised VERDICT-MRI for Enhanced Prostate Tumour Characterisation

MRI is increasingly being used in the diagnosis of prostate cancer (PCa)...

0 Snigdha Sen, et al. ∙

∙ 11/18/2022

Weighted Ensemble Self-Supervised Learning

Ensembling has proven to be a powerful technique for boosting model perf...

0 Yangjun Ruan, et al. ∙

∙ 04/06/2022

LilNetX: Lightweight Networks with EXtreme Model Compression and Structured Sparsification

We introduce LilNetX, an end-to-end trainable technique for neural netwo...

0 Sharath Girish, et al. ∙

∙ 04/26/2021

3D Scene Compression through Entropy Penalized Neural Representation Functions

Some forms of novel visual media enable the viewer to explore a 3D scene...

7 Thomas Bird, et al. ∙

∙ 09/12/2020

A Review on Cyber Crimes on the Internet of Things

Internet of Things (IoT) devices are rapidly becoming universal. The suc...

0 Mohan Krishna Kagita, et al. ∙

∙ 08/26/2020

An Approximate Carry Estimating Simultaneous Adder with Rectification

Approximate computing has in recent times found significant applications...

0 Rajat Bhattacharjya, et al. ∙

∙ 07/23/2020

End-to-end Learning of Compressible Features

Pre-trained convolutional neural networks (CNNs) are powerful off-the-sh...

16 Saurabh Singh, et al. ∙

∙ 07/17/2020

Channel-wise Autoregressive Entropy Models for Learned Image Compression

In learning-based approaches to image compression, codecs are developed ...

11 David Minnen, et al. ∙

∙ 07/06/2020

Nonlinear Transform Coding

We review a class of methods that can be collected under the name nonlin...

0 Johannes Ballé, et al. ∙

∙ 05/18/2020

Deep Implicit Volume Compression

We describe a novel approach for compressing truncated signed distance f...

1 Danhang Tang, et al. ∙

∙ 04/07/2020

PatchVAE: Learning Local Latent Codes for Recognition

Unsupervised representation learning holds the promise of exploiting lar...

5 Kamal Gupta, et al. ∙

∙ 11/21/2019

Filter Response Normalization Layer: Eliminating Batch Dependence in the Training of Deep Neural Networks

Batch Normalization (BN) is a highly successful and widely used batch de...

0 Saurabh Singh, et al. ∙

∙ 06/15/2019

Model Compression by Entropy Penalized Reparameterization

We describe an end-to-end neural network weight compression approach tha...

0 Deniz Oktay, et al. ∙

∙ 04/12/2019

EvalNorm: Estimating Batch Normalization Statistics for Evaluation

Batch normalization (BN) has been very effective for deep learning and i...

0 Saurabh Singh, et al. ∙

∙ 05/31/2018

Image-Dependent Local Entropy Models for Learned Image Compression

The leading approach for image compression with artificial neural networ...

0 David Minnen, et al. ∙

∙ 02/07/2018

Spatially adaptive image compression using a tiled deep network

Deep neural networks represent a powerful class of function approximator...

0 David Minnen, et al. ∙

∙ 02/01/2018

Variational image compression with a scale hyperprior

We describe an end-to-end trainable model for image compression based on...

0 Johannes Ballé, et al. ∙

∙ 07/25/2017

All that is English may be Hindi: Enhancing language identification through automatic ranking of likeliness of word borrowing in social media

In this paper, we present a set of computational methods to identify the...

0 Jasabanta Patro, et al. ∙

∙ 07/10/2017

Revisiting Unreasonable Effectiveness of Data in Deep Learning Era

The success of deep learning in vision can be attributed to: (a) models ...

0 Chen Sun, et al. ∙

∙ 05/18/2017

Target-Quality Image Compression with Recurrent, Convolutional Neural Networks

We introduce a stop-code tolerant (SCT) approach to training recurrent c...

0 Michele Covell, et al. ∙

∙ 04/02/2017

Aligned Image-Word Representations Improve Inductive Transfer Across Vision-Language Tasks

An important goal of computer vision is to build systems that learn visu...

0 Tanmay Gupta, et al. ∙

∙ 03/29/2017

Improved Lossy Image Compression with Priming and Spatially Adaptive Bit Rates for Recurrent Networks

We propose a method for lossy image compression based on recurrent, conv...

0 Nick Johnston, et al. ∙

∙ 03/21/2017

No Fuss Distance Metric Learning using Proxies

We address the problem of distance metric learning (DML), defined as lea...

0 Yair Movshovitz-Attias, et al. ∙

∙ 03/15/2017

Is this word borrowed? An automatic approach to quantify the likeliness of borrowing in social media

Code-mixing or code-switching are the effortless phenomena of natural sw...

0 Jasabanta Patro, et al. ∙

∙ 05/20/2016

Swapout: Learning an ensemble of deep architectures

We describe Swapout, a new stochastic training method, that outperforms ...

0 Saurabh Singh, et al. ∙

∙ 07/22/2015

Part Localization using Multi-Proposal Consensus for Fine-Grained Categorization

We present a simple deep learning framework to simultaneously predict ke...

0 Kevin J. Shih, et al. ∙

∙ 05/14/2012

Unsupervised Discovery of Mid-Level Discriminative Patches

The goal of this paper is to discover a set of discriminative patches wh...

0 Saurabh Singh, et al. ∙

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