A5103172155- Advanced Neural Network Applications
- Remote-Sensing Image Classification
- Remote Sensing and Land Use
- Advanced Image and Video Retrieval Techniques
- Land Use and Ecosystem Services
- Adversarial Robustness in Machine Learning
- Medical Image Segmentation Techniques
- Bipolar Disorder and Treatment
- Cannabis and Cannabinoid Research
- Digital Image Processing Techniques
- Generative Adversarial Networks and Image Synthesis
- Heat Transfer Mechanisms
- Digital Innovation in Industries
- CCD and CMOS Imaging Sensors
- Trauma and Emergency Care Studies
- Solar Thermal and Photovoltaic Systems
- COVID-19 diagnosis using AI
- Data Management and Algorithms
- Recommender Systems and Techniques
- Fault Detection and Control Systems
- Dialysis and Renal Disease Management
- Maritime Navigation and Safety
- Aerodynamics and Fluid Dynamics Research
- Ethics and Social Impacts of AI
- Automated Road and Building Extraction
Terna Dental College and Hospital
2021
Institute of Medical Sciences
2015-2021
Government Medical College, Amritsar
2021
Saints Cyril and Methodius University of Skopje
2021
University of Cincinnati Medical Center
2021
Larkin Community Hospital
2021
Yenepoya University
2021
Windsor University School of Medicine
2021
University of Health Sciences Lahore
2021
University of Cincinnati
2021
The advent of multitemporal high resolution data, like the Copernicus Sentinel-2, has enhanced significantly potential monitoring earth's surface and environmental dynamics. In this paper, we present a novel deep learning framework for urban change detection which combines state-of-the-art fully convolutional networks (similar to U-Net) feature representation powerful recurrent (such as LSTMs) temporal modeling. We report our results on recently publicly available bi-temporal Onera Satellite...
Chatbot is a computer application that interacts with users using natural language in similar way to imitate human travel agent. A successful implementation of chatbot system can analyze user preferences and predict collective intelligence. In most cases, it provide better user-centric recommendations. Hence, the becoming an integral part future consumer services. This paper intelligent domain on Echo platform which would gather model knowledge base recommend Restricted Boltzmann Machine...
The 1 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">st</sup> Workshop on Maritime Computer Vision (MaCVi) 2023 focused maritime computer vision for Unmanned Aerial Vehicles (UAV) and Surface Vehicle (USV), organized several subchallenges in this domain: (i) UAV-based Object Detection, (ii) Mar-itime Tracking, (iii) USV-based Obstacle Segmentation (iv) Detection. were based the SeaDronesSee MODS benchmarks. This report summarizes main findings...
This article explores the critical ethical considerations surrounding AI-driven personalization in eCommerce platforms. It delves into complexities of privacy and data protection, examining challenges collection practices regulatory compliance an increasingly data-driven marketplace. The paper addresses pervasive issue algorithmic bias, discussing its potential impacts on product recommendations pricing, while proposing methods for detection mitigation. Transparency accountability AI systems...
Connected Component Labeling (CCL) is one of the most important step in pattern recognition and image processing. It assigns labels to pixels such that adjacent sharing same features are assigned label. Typically, CCL requires several passes over data. We focus on two-pass technique where each pixel given a provisional label first pass whereas an actual second pass. present scalable parallel algorithm, called PAREMSP, which employs scan strategy best union-find REMSP, uses REM'S algorithm...
Detecting change through multi-image, multi-date remote sensing is essential to developing and understanding of global conditions. Despite recent advancements in realized deep learning, novel methods for accurate multi-image detection remain unrealized. Recently, several promising have been proposed address this topic, but a paucity publicly available data limits the that can be assessed. In particular, there exists limited work on categorizing nature status across an observation period.This...
We define the crossing graph of a given embedded (such as road network) to be with vertex for each edge embedding, two vertices adjacent when corresponding edges embedding cross other. In this paper, we study sparsity properties graphs real-world networks. show that, in large networks (the Urban Road Network Dataset), have connected components that are primarily trees, and remaining non-tree typically sparse (technically, they bounded degeneracy). prove theoretically an has graph, it other...
Geospatial machine learning has seen tremendous aca-demic advancement, but its practical application been constrained by difficulties with operationalizing performant and reliable solutions. Sourcing satellite imagery in real-world settings, handling terabytes of training data, managing artifacts are a few the chal-lenges that have severely limited downstream innovation. In this paper we introduce GeoEngine <sup xmlns:mml="http://www.w3.org/1998/Math/MathML"...
Deep Neural Networks are one of the machine learning techniques which increasingly used in a variety applications. However, significantly high memory and computation demands deep neural networks often limit their deployment on embedded systems. Many recent works have considered this problem by proposing different types data quantization schemes. most these either require post-quantization retraining or bear significant loss output accuracy. In paper, we propose novel scalable technique with...
In this paper we introduce a novel platform for teams to develop rich, analysis-ready datasets geospatial machine learning. Europa <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> https://europa.granular.ai addresses longstanding challenges that remote sensing and vision researchers face when developing datasets, including data sourcing, dataset development sharing. By simplifying accelerating the creation process, serves expedite pace of...
Deep Neural Networks are one of the machine learning techniques which increasingly used in a variety applications. However, significantly high memory and computation demands deep neural networks often limit their deployment on embedded systems. Many recent works have considered this problem by proposing different types data quantization schemes. most these either require post-quantization retraining or bear significant loss output accuracy. In paper, we propose novel technique for parameters...
Objectives To determine the demographic predictors of suicidal behaviors and measure association between spectrum substance use disorders (SUD) hospitalization for in adolescent population. Methods We conducted a cross-sectional study using nationwide inpatient sample included 466,244 inpatients with psychiatric illnesses. The was sub-grouped into (N = 182,454) non-suicidal 283,790) cohorts. odds ratio (OR) characteristics comorbid SUD group evaluated logistic regression model P-value <...
Objectives To evaluate the difference in demographics and clinical correlates during hospitalization for chronic kidney disease (CKD) between patients with depression those without depression, its impact on severity of illness in-hospital mortality. Methods We conducted a case-control study included 2,296 adult inpatients (age ≥18 years) primary discharge diagnosis CKD using nationwide inpatient sample (NIS). used propensity score matching to extract cases i.e., (N = 1,264) controls i.e....
Objectives To explore the independent association between cannabis abuse and subsequent hospitalizations for acute pancreatitis (AP) delineate demographic differences among AP in patients with without persistent abuse. Methods We conducted a retrospective cross-sectional study using nationwide inpatient sample included 50,444,133 (age 18-50 years) primary discharge diagnosis medical illnesses further grouped by presence of (N = 666,248). used logistic regression model to measure odds ratio...