Search Results for author: Nilanjan Ray

Found 40 papers, 22 papers with code

Learning Diffeomorphism for Image Registration with Time-Continuous Networks using Semigroup Regularization

1 code implementation29 May 2024 Mohammadjavad Matinkia, Nilanjan Ray

As one of the fundamental properties of flow maps, we exploit the semigroup property as the only form of regularization, ensuring temporally continuous diffeomorphic flows between pairs of images.

Image Registration

Disentangling Hippocampal Shape Variations: A Study of Neurological Disorders Using Graph Variational Autoencoder with Contrastive Learning

1 code implementation31 Mar 2024 Jakaria Rabbi, Johannes Kiechle, Christian Beaulieu, Nilanjan Ray, Dana Cobzas

This research provides valuable insights into the relationship between neurological disorder and hippocampal shape changes in different age groups of MS populations using a Graph VAE with Supervised Contrastive loss.

Attribute Contrastive Learning +2

ShadowSense: Unsupervised Domain Adaptation and Feature Fusion for Shadow-Agnostic Tree Crown Detection from RGB-Thermal Drone Imagery

1 code implementation24 Oct 2023 Rudraksh Kapil, Seyed Mojtaba Marvasti-Zadeh, Nadir Erbilgin, Nilanjan Ray

Accurate detection of individual tree crowns from remote sensing data poses a significant challenge due to the dense nature of forest canopy and the presence of diverse environmental variations, e. g., overlapping canopies, occlusions, and varying lighting conditions.

Unsupervised Domain Adaptation

Predicting Ki67, ER, PR, and HER2 Statuses from H&E-stained Breast Cancer Images

no code implementations3 Aug 2023 Amir Akbarnejad, Nilanjan Ray, Penny J. Barnes, Gilbert Bigras

In a quest to answer this question, we built a large-scale dataset (185538 images) with reliable measurements for Ki67, ER, PR, and HER2 statuses.

Binary Classification

Document Image Cleaning using Budget-Aware Black-Box Approximation

1 code implementation22 Jun 2023 Ganesh Tata, Katyani Singh, Eric Van Oeveren, Nilanjan Ray

In this work, we propose two sample selection algorithms to train an OCR preprocessor with less than 10% of the original system's OCR engine queries, resulting in more than 60% reduction of the total training time without significant loss of accuracy.

Optical Character Recognition (OCR)

Towards Early Prediction of Human iPSC Reprogramming Success

1 code implementation23 May 2023 Abhineet Singh, Ila Jasra, Omar Mouhammed, Nidheesh Dadheech, Nilanjan Ray, James Shapiro

This paper presents advancements in automated early-stage prediction of the success of reprogramming human induced pluripotent stem cells (iPSCs) as a potential source for regenerative cell therapies. The minuscule success rate of iPSC-reprogramming of around $ 0. 01% $ to $ 0. 1% $ makes it labor-intensive, time-consuming, and exorbitantly expensive to generate a stable iPSC line.

Cell Segmentation

Weakly Supervised Realtime Dynamic Background Subtraction

no code implementations6 Mar 2023 Fateme Bahri, Nilanjan Ray

In this work, we propose a weakly supervised framework that can perform background subtraction without requiring per-pixel ground-truth labels.

Object Tracking

Crown-CAM: Interpretable Visual Explanations for Tree Crown Detection in Aerial Images

no code implementations23 Nov 2022 Seyed Mojtaba Marvasti-Zadeh, Devin Goodsman, Nilanjan Ray, Nadir Erbilgin

Visual explanation of ``black-box'' models allows researchers in explainable artificial intelligence (XAI) to interpret the model's decisions in a human-understandable manner.

Explainable artificial intelligence Explainable Artificial Intelligence (XAI)

Early Detection of Bark Beetle Attack Using Remote Sensing and Machine Learning: A Review

no code implementations7 Oct 2022 Seyed Mojtaba Marvasti-Zadeh, Devin Goodsman, Nilanjan Ray, Nadir Erbilgin

This paper provides a comprehensive review of past and current advances in the early detection of bark beetle-induced tree mortality from three primary perspectives: bark beetle & host interactions, RS, and ML/DL.


Unsupervised diffeomorphic cardiac image registration using parameterization of the deformation field

no code implementations28 Aug 2022 Ameneh Sheikhjafari, Deepa Krishnaswamy, Michelle Noga, Nilanjan Ray, Kumaradevan Punithakumar

Finally, it is suitable for cardiac data processing, since the nature of this parameterization is to define the deformation field in terms of the radial and rotational components.

Image Registration

Learning-based Monocular 3D Reconstruction of Birds: A Contemporary Survey

no code implementations10 Jul 2022 Seyed Mojtaba Marvasti-Zadeh, Mohammad N. S. Jahromi, Javad Khaghani, Devin Goodsman, Nilanjan Ray, Nadir Erbilgin

In nature, the collective behavior of animals, such as flying birds is dominated by the interactions between individuals of the same species.

3D Reconstruction Image to 3D +1

Dynamic Background Subtraction by Generative Neural Networks

1 code implementation10 Feb 2022 Fateme Bahri, Nilanjan Ray

One of the challenges for background subtraction methods is dynamic background, which constitute stochastic movements in some parts of the background.

Towards Positive Jacobian: Learn to Postprocess Diffeomorphic Image Registration with Matrix Exponential

1 code implementation1 Feb 2022 Soumyadeep Pal, Matthew Tennant, Nilanjan Ray

We present a postprocessing layer for deformable image registration to make a registration field more diffeomorphic by encouraging Jacobians of the transformation to be positive.

Image Registration

A training-free recursive multiresolution framework for diffeomorphic deformable image registration

no code implementations1 Feb 2022 Ameneh Sheikhjafari, Michelle Noga, Kumaradevan Punithakumar, Nilanjan Ray

The moving image is warped successively at each resolution and finally aligned to the fixed image; this procedure is recursive in a way that at each resolution, a fully convolutional network (FCN) models a progressive change of deformation for the current warped image.

Image Registration

GPEX, A Framework For Interpreting Artificial Neural Networks

1 code implementation NeurIPS 2023 Amir Akbarnejad, Gilbert Bigras, Nilanjan Ray

Using our method we find out that on 5 datasets, only a subset of those theoretical assumptions are sufficient.

Gaussian Processes

Unknown-box Approximation to Improve Optical Character Recognition Performance

1 code implementation17 May 2021 Ayantha Randika, Nilanjan Ray, Xiao Xiao, Allegra Latimer

Unlike the previous OCR agnostic preprocessing techniques, the proposed approach approximates the gradient of a particular OCR engine to train a preprocessor module.

Optical Character Recognition Optical Character Recognition (OCR)

Locating Cephalometric X-Ray Landmarks with Foveated Pyramid Attention

1 code implementation MIDL 2019 Logan Gilmour, Nilanjan Ray

For very large images, this makes training untenable, as the memory and computation required for activation maps scales quadratically with the side length of an image.


Ordinary Differential Equation and Complex Matrix Exponential for Multi-resolution Image Registration

1 code implementation27 Jul 2020 Abhishek Nan, Matthew Tennant, Uriel Rubin, Nilanjan Ray

Autograd-based software packages have recently renewed interest in image registration using homography and other geometric models by gradient descent and optimization, e. g., AirLab and DRMIME.

Image Registration

To Filter Prune, or to Layer Prune, That Is The Question

1 code implementation11 Jul 2020 Sara Elkerdawy, Mostafa Elhoushi, Abhineet Singh, Hong Zhang, Nilanjan Ray

LayerPrune presents a set of layer pruning methods based on different criteria that achieve higher latency reduction than filter pruning methods on similar accuracy.

Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network

4 code implementations20 Mar 2020 Jakaria Rabbi, Nilanjan Ray, Matthias Schubert, Subir Chowdhury, Dennis Chao

Inspired by the success of edge enhanced GAN (EEGAN) and ESRGAN, we apply a new edge-enhanced super-resolution GAN (EESRGAN) to improve the image quality of remote sensing images and use different detector networks in an end-to-end manner where detector loss is backpropagated into the EESRGAN to improve the detection performance.

Generative Adversarial Network Image Enhancement +6

Animal Detection in Man-made Environments

1 code implementation24 Oct 2019 Abhineet Singh, Marcin Pietrasik, Gabriell Natha, Nehla Ghouaiel, Ken Brizel, Nilanjan Ray

Automatic detection of animals that have strayed into human inhabited areas has important security and road safety applications.

Edge Detection object-detection +3

Lightweight Monocular Depth Estimation Model by Joint End-to-End Filter pruning

1 code implementation13 May 2019 Sara Elkerdawy, Hong Zhang, Nilanjan Ray

This is achieved by removing the least important features with a novel joint end-to-end filter pruning.

Monocular Depth Estimation

Fine-Grained Vehicle Classification with Unsupervised Parts Co-occurrence Learning

no code implementations23 Jan 2019 Sara Elkerdawy, Nilanjan Ray, Hong Zhang

In addition, we achieve 95. 5% and 93. 19% on CompCars on both train-test splits, 70-30 and 50-50, outperforming the other methods by 4. 5% and 8% respectively.

Classification Fine-Grained Image Classification +3

River Ice Segmentation with Deep Learning

2 code implementations14 Jan 2019 Abhineet Singh, Hayden Kalke, Mark Loewen, Nilanjan Ray

This paper deals with the problem of computing surface ice concentration for two different types of ice from digital images of river surface.

Segmentation Semantic Segmentation

End-to-end Learning of Convolutional Neural Net and Dynamic Programming for Left Ventricle Segmentation

1 code implementation MIDL 2019 Nhat M. Nguyen, Nilanjan Ray

Differentiable programming is able to combine different functions or programs in a processing pipeline with the goal of applying end-to-end learning or optimization.

Left Ventricle Segmentation

Online Illumination Invariant Moving Object Detection by Generative Neural Network

no code implementations3 Aug 2018 Fateme Bahri, Moein Shakeri, Nilanjan Ray

In this paper, we propose an extension of a state-of-the-art batch MOD method (ILISD) to an online/incremental MOD using unsupervised and generative neural networks, which use illumination invariant image representations.

Moving Object Detection object-detection

Generative Adversarial Networks using Adaptive Convolution

no code implementations ICLR 2018 Nhat M. Nguyen, Nilanjan Ray

Most existing GANs architectures that generate images use transposed convolution or resize-convolution as their upsampling algorithm from lower to higher resolution feature maps in the generator.

Cell Detection in Microscopy Images with Deep Convolutional Neural Network and Compressed Sensing

3 code implementations10 Aug 2017 Yao Xue, Nilanjan Ray

In this paper, we seek a different route and propose a convolutional neural network (CNN)-based cell detection method that uses encoding of the output pixel space.

Cell Detection

Face Recognition using Multi-Modal Low-Rank Dictionary Learning

no code implementations15 Mar 2017 Homa Foroughi, Moein Shakeri, Nilanjan Ray, Hong Zhang

Face recognition has been widely studied due to its importance in different applications; however, most of the proposed methods fail when face images are occluded or captured under illumination and pose variations.

Dictionary Learning Face Recognition +1

Object Classification with Joint Projection and Low-rank Dictionary Learning

no code implementations5 Dec 2016 Homa Foroughi, Nilanjan Ray, Hong Zhang

To address these issues, we propose a joint projection and low-rank dictionary learning method using dual graph constraints (JP-LRDL).

Classification Dictionary Learning +1

Deep Deformable Registration: Enhancing Accuracy by Fully Convolutional Neural Net

no code implementations27 Nov 2016 Sayan Ghosal, Nilanjan Ray

Next, we minimize this UB-SSD by adjusting both the parameters of the FCNN and the parameters of the deformable model in coordinate descent.

Recurrent Fully Convolutional Networks for Video Segmentation

no code implementations1 Jun 2016 Sepehr Valipour, Mennatullah Siam, Martin Jagersand, Nilanjan Ray

Accordingly, we propose a novel method for online segmentation of video sequences that incorporates temporal data.

Change Detection Image Segmentation +4

Joint Projection and Dictionary Learning using Low-rank Regularization and Graph Constraints

no code implementations24 Mar 2016 Homa Foroughi, Nilanjan Ray, Hong Zhang

To address this issue, we propose a joint projection and dictionary learning using low-rank regularization and graph constraints (JPDL-LR).

Dictionary Learning Dimensionality Reduction +2

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