Search Results for author: Deval Mehta

Found 10 papers, 2 papers with code

Revamping AI Models in Dermatology: Overcoming Critical Challenges for Enhanced Skin Lesion Diagnosis

no code implementations2 Nov 2023 Deval Mehta, Brigid Betz-Stablein, Toan D Nguyen, Yaniv Gal, Adrian Bowling, Martin Haskett, Maithili Sashindranath, Paul Bonnington, Victoria Mar, H Peter Soyer, ZongYuan Ge

For a clinical image, our model generates three outputs: a hierarchical prediction, an alert for out-of-distribution images, and a recommendation for dermoscopy if clinical image alone is insufficient for diagnosis.

Privacy-preserving Early Detection of Epileptic Seizures in Videos

no code implementations15 Sep 2023 Deval Mehta, Shobi Sivathamboo, Hugh Simpson, Patrick Kwan, Terence O`Brien, ZongYuan Ge

In this work, we contribute towards the development of video-based epileptic seizure classification by introducing a novel framework (SETR-PKD), which could achieve privacy-preserved early detection of seizures in videos.

Knowledge Distillation Optical Flow Estimation +2

TPMIL: Trainable Prototype Enhanced Multiple Instance Learning for Whole Slide Image Classification

1 code implementation1 May 2023 Litao Yang, Deval Mehta, Sidong Liu, Dwarikanath Mahapatra, Antonio Di Ieva, ZongYuan Ge

Due to the high resolution of the WSI and the unavailability of patch-level annotations, WSI classification is usually formulated as a weakly supervised problem, which relies on multiple instance learning (MIL) based on patches of a WSI.

Image Classification Multiple Instance Learning +1

Multi-dimensional Racism Classification during COVID-19: Stigmatization, Offensiveness, Blame, and Exclusion

no code implementations29 Aug 2022 Xin Pei, Deval Mehta

With the aid of BERT and topic modeling, this categorical detection enables insights into the underlying subtlety of racist discussion on digital platforms during COVID-19.

Leukocyte Classification using Multimodal Architecture Enhanced by Knowledge Distillation

no code implementations17 Aug 2022 Litao Yang, Deval Mehta, Dwarikanath Mahapatra, ZongYuan Ge

Our unique contribution is two-fold - 1) We present a first of its kind multimodal WBC dataset for WBC classification; 2) We develop a high performing multimodal architecture which is also efficient and low in complexity at the same time.

Classification Knowledge Distillation

Beyond a binary of (non)racist tweets: A four-dimensional categorical detection and analysis of racist and xenophobic opinions on Twitter in early Covid-19

no code implementations18 Jul 2021 Xin Pei, Deval Mehta

Transcending the binary categorization of racist and xenophobic texts, this research takes cues from social science theories to develop a four dimensional category for racism and xenophobia detection, namely stigmatization, offensiveness, blame, and exclusion.

Towards Automated and Marker-less Parkinson Disease Assessment: Predicting UPDRS Scores using Sit-stand videos

no code implementations10 Apr 2021 Deval Mehta, Umar Asif, Tian Hao, Erhan Bilal, Stefan von Cavallar, Stefan Harrer, Jeffrey Rogers

For BRADY we find F1-scores of 0. 75 using our framework compared to 0. 50 for the video based rater clinicians, while for PIGD we find 0. 78 for the framework and 0. 45 for the video based rater clinicians.

DeepActsNet: Spatial and Motion features from Face, Hands, and Body Combined with Convolutional and Graph Networks for Improved Action Recognition

no code implementations21 Sep 2020 Umar Asif, Deval Mehta, Stefan von Cavallar, Jianbin Tang, Stefan Harrer

Existing action recognition methods mainly focus on joint and bone information in human body skeleton data due to its robustness to complex backgrounds and dynamic characteristics of the environments.

Action Recognition

#Coronavirus or #Chinesevirus?!: Understanding the negative sentiment reflected in Tweets with racist hashtags across the development of COVID-19

no code implementations17 May 2020 Xin Pei, Deval Mehta

Situated in the global outbreak of COVID-19, our study enriches the discussion concerning the emergent racism and xenophobia on social media.

Keyword Extraction Sentiment Analysis

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