Search Results for author: Sohini Roychowdhury

Found 21 papers, 7 papers with code

Journey of Hallucination-minimized Generative AI Solutions for Financial Decision Makers

no code implementations18 Nov 2023 Sohini Roychowdhury

In this work we present the three major stages in the journey of designing hallucination-minimized LLM-based solutions that are specialized for the decision makers of the financial domain, namely: prototyping, scaling and LLM evolution using human feedback.

Answer Generation Decision Making +2

NUMSnet: Nested-U Multi-class Segmentation network for 3D Medical Image Stacks

no code implementations5 Apr 2023 Sohini Roychowdhury

In this work, we present a novel variant of the Unet model called the NUMSnet that transmits pixel neighborhood features across scans through nested layers to achieve accurate multi-class semantic segmentations with minimal training data.

Segmentation Semantic Segmentation +1

Semi-supervised and Deep learning Frameworks for Video Classification and Key-frame Identification

no code implementations25 Mar 2022 Sohini Roychowdhury

Automating video-based data and machine learning pipelines poses several challenges including metadata generation for efficient storage and retrieval and isolation of key-frames for scene understanding tasks.

Retrieval Scene Understanding +1

QU-net++: Image Quality Detection Framework for Segmentation of Medical 3D Image Stacks

1 code implementation27 Oct 2021 Sohini Roychowdhury

In this work, we propose an automated two-step method that detects a minimal image subset required to train segmentation models by evaluating the quality of medical images from 3D image stacks using a U-net++ model.

Segmentation Semantic Segmentation

Video-Data Pipelines for Machine Learning Applications

1 code implementation15 Oct 2021 Sohini Roychowdhury, James Y. Sato

In this work, we present a data pipeline framework that can automate this process of manual frame sifting in video sequences by controlling the fraction of frames that can be removed based on image quality and content type.

Autonomous Driving BIG-bench Machine Learning +3

SISE-PC: Semi-supervised Image Subsampling for Explainable Pathology

1 code implementation23 Feb 2021 Sohini Roychowdhury, Kwok Sun Tang, Mohith Ashok, Anoop Sanka

We propose a novel active learning framework that identifies a minimal sub-sampled dataset containing the most uncertain OCT image samples using label propagation on the SimCLR latent encodings.

Active Learning General Classification

OPAM: Online Purchasing-behavior Analysis using Machine learning

1 code implementation2 Feb 2021 Sohini Roychowdhury, Ebrahim Alareqi, Wenxi Li

To support the recent increase in online shopping trends, in this work, we present a customer purchasing behavior analysis system using supervised, unsupervised and semi-supervised learning methods.

BIG-bench Machine Learning Partial Label Learning

Cirrus: A Long-range Bi-pattern LiDAR Dataset

no code implementations5 Dec 2020 Ze Wang, Sihao Ding, Ying Li, Jonas Fenn, Sohini Roychowdhury, Andreas Wallin, Lane Martin, Scott Ryvola, Guillermo Sapiro, Qiang Qiu

Point density varies significantly across such a long range, and different scanning patterns further diversify object representation in LiDAR.

3D Object Detection Autonomous Driving +2

Categorizing Online Shopping Behavior from Cosmetics to Electronics: An Analytical Framework

1 code implementation6 Oct 2020 Sohini Roychowdhury, Wenxi Li, Ebrahim Alareqi, Akhilesh Pandita, Ao Liu, Joakim Soderberg

A success factor for modern companies in the age of Digital Marketing is to understand how customers think and behave based on their online shopping patterns.

Descriptive Marketing

Few Shot Learning Framework to Reduce Inter-observer Variability in Medical Images

3 code implementations7 Aug 2020 Sohini Roychowdhury

Also, the proposed framework with ParESN model minimizes manual annotation checking to 12-28% of the total number of images.

Few-Shot Learning

Range Adaptation for 3D Object Detection in LiDAR

no code implementations26 Sep 2019 Ze Wang, Sihao Ding, Ying Li, Minming Zhao, Sohini Roychowdhury, Andreas Wallin, Guillermo Sapiro, Qiang Qiu

To the best of our knowledge, this paper is the first attempt to study cross-range LiDAR adaptation for object detection in point clouds.

3D Object Detection Autonomous Driving +2

Automated OCT Segmentation for Images with DME

no code implementations24 Oct 2016 Sohini Roychowdhury, Dara D. Koozekanani, Michael Reinsbach, Keshab K. Parhi

For estimating the sub-retinal layer thicknesses, the proposed system has an average error of 0. 2-2. 5 $\mu m$ and 1. 8-18 $\mu m$ in normal and abnormal images, respectively.

Denoising

Automated Selection of Uniform Regions for CT Image Quality Detection

no code implementations13 Aug 2016 Maitham D Naeemi, Adam M Alessio, Sohini Roychowdhury

In the proposed method, two windowed CT image subset regions are analyzed together to identify the extent of variation in the corresponding Fourier-domain spectrum.

Blind Analysis of CT Image Noise Using Residual Denoised Images

no code implementations24 May 2016 Sohini Roychowdhury, Nathan Hollraft, Adam Alessio

Methods: We propose novel performance metrics corresponding to the accuracy of noise and signal estimation.

Noise Estimation

A generalized flow for multi-class and binary classification tasks: An Azure ML approach

no code implementations26 Mar 2016 Matthew Bihis, Sohini Roychowdhury

The classification characteristics of the proposed flow are comparatively evaluated on 3 public data sets and a local data set with respect to existing state-of-the-art methods.

Binary Classification Classification +3

Classification of Large-Scale Fundus Image Data Sets: A Cloud-Computing Framework

no code implementations26 Mar 2016 Sohini Roychowdhury

For images from the DIARETDB1 data set, 40 of its highest-ranked features are used to classify four DR lesion types with an average classification accuracy of 90. 1% in 792 seconds.

Classification Cloud Computing +1

Facial Expression Detection using Patch-based Eigen-face Isomap Networks

no code implementations11 Nov 2015 Sohini Roychowdhury

Automated facial expression detection problem pose two primary challenges that include variations in expression and facial occlusions (glasses, beard, mustache or face covers).

Classification Clustering +1

A Survey of the Trends in Facial and Expression Recognition Databases and Methods

no code implementations7 Nov 2015 Sohini Roychowdhury, Michelle Emmons

The evolution trends in databases and methodologies for facial and expression recognition can be useful for assessing the next-generation topics that may have applications in security systems or personal identification systems that involve "Quantitative face" assessments.

Facial Expression Recognition Facial Expression Recognition (FER)

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