K. Palaniappan

K. Palaniappan
University of Missouri | Mizzou · Department of Computer Science and IT

About

532
Publications
126,179
Reads
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26,583
Citations
Introduction
Dr. Palaniappan is a professor of Electrical Engineering and Computer Science at the University of Missouri. His current research interests funded by NIH, DoD, NSF, and NASA include computer vision, deep learning, AI, cloud computing, parallelization, data visualization, remote sensing and biomedical image analysis. National awards include National Academy of Sciences Jefferson Science Fellowship and the NASA Public Service Medal for big data visualization. At NASA GSFC he co-founded the Visualization Analysis Lab and co-developed the Interactive Image SpreadSheet for very large imagery. At the University of Missouri he established the Computational Imaging and Vis-Analysis Laboratory.
Additional affiliations
January 1998 - December 2013
University of Missouri
January 1991 - December 1996
January 1991 - December 1996
NASA
Position
  • NASA GSFC
Education
January 1986 - December 1990
University of Illinois, Urbana-Champaign
Field of study
  • Electrical and Computer Engineering
January 1986 - December 1990
University of Illinois, Urbana-Champaign
Field of study
  • Electrical and Computer Engineering

Publications

Publications (532)
Article
The vocal folds (VFs) are a pair of muscles in the larynx that play a critical role in breathing, swallowing, and speaking. VF function can be adversely affected by various medical conditions including head or neck injuries, stroke, tumor, and neurological disorders. In this paper, we propose a deep learning system for automated detection of laryng...
Article
Full-text available
Understanding and controlling the self-assembly of vertically oriented carbon nanotube (CNT) forests is essential for realizing their potential in myriad applications. The governing process–structure–property mechanisms are poorly understood, and the processing parameter space is far too vast to exhaustively explore experimentally. We overcome thes...
Conference Paper
While the physical properties of carbon nanotubes (CNTs) are often superior to conventional engineering materials, their widespread adoption into many applications is limited by scaling the properties of individual CNTs to macroscale CNT assemblies known as CNT forests. The self-assembly mechanics of CNT forests that determine their morphology and...
Conference Paper
Accurate segmentation and tracking of cells in microscopy image sequences is extremely beneficial in clinical diagnostic applications and biomedical research. A continuing challenge is the segmentation of dense touching cells and deforming cells with indistinct boundaries, in low signal-to-noise-ratio images. In this paper, we present a dual-stream...
Article
Detection, segmentation, and quantification of microvascular structures are the main steps towards studying microvascular remodeling. Combined with appropriate staining, confocal microscopy imaging enables exploration of the full 3D anatomical characteristics of microvascular systems. Segmentation of confocal microscopy images is a challenging task...
Article
Analysis of morphometric features of nuclei plays an important role in understanding disease progression and predict efficacy of treatment. First step towards this goal requires segmentation of individual nuclei within the imaged tissue. Accurate nuclei instance segmentation is one of the most challenging tasks in computational pathology due to bro...
Article
Key points: Microvascular network architecture defines coupling of fluid and protein exchange. Network arrangements markedly reduce capillary hydrostatic pressures and resting fluid movement while increasing the capacity for change The presence of vascular remodelling or angiogenesis puts constraints of network behaviour The sites of fluid and pro...
Article
Full-text available
Precise positioning of neurons resulting from cell division and migration during development is critical for normal brain function. Disruption of neuronal migration can cause a myriad of neurological disorders. To investigate the functional consequences of defective neuronal positioning on circuit function, we studied a zebrafish frizzled3a (fzd3a)...
Article
Multi-Unmanned Aerial Vehicle (UAV) systems with high-resolution cameras have been found useful for operations such as smart city and disaster management. These systems feature Flying Ad-Hoc Networks (FANETs) that connect the computation edge with UAVs and a Ground Control Station (GCS) through air-to-ground wireless network links. Leveraging the e...
Article
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The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this approach to >10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans, including metagenomes from human and a...
Article
Full-text available
A Correction to this paper has been published: https://doi.org/10.1038/s41587-021-00898-4.
Chapter
3D city-scale point cloud stitching is a critical component for large data collection, environment change detection, in which massive amounts of 3D data are captured under different times and conditions. This paper proposes a novel point cloud stitching approach, that automatically and accurately stitches multiple city-scale point clouds, which onl...
Conference Paper
Full-text available
Characterizing the spatial relationship between the blood vessels and lymphatic vascular structures, in the mice dura mater tissue, is useful for modeling fluid flows and changes in dynamics in various disease processes. We propose a new deep learning-based approach to fuse a set of multi-channel single-focus microscopy images within each volumetri...
Conference Paper
In this paper we introduce a novel end-to-end framework for generation of large, aerial, city-scale, realistic synthetic image sequences with associated accurate and precise camera metadata. The two main purposes for this data are (i) to enable objective, quantitative evaluation of computer vision algorithms and methods such as feature detection, d...
Article
Ubiquitous low cost multi-rotor and fixed wing drones or unmanned aerial vehicles (UAVs) have accelerated the need for reliable, robust, and scalable Structure-from-Motion (SfM) and Multi-View Stereo (MVS) pipelines suitable for a variety of flightpath trajectories especially in degraded environments. Feature tracking being a core part of SfM and M...
Article
Full-text available
Background Light microscopy is often used for malaria diagnosis in the field. However, it is time-consuming and quality of the results depends heavily on the skill of microscopists. Automating malaria light microscopy is a promising solution, but it still remains a challenge and an active area of research. Current tools are often expensive and invo...
Article
Viruses are integral components of all ecosystems and microbiomes on Earth. Through pervasive infections of their cellular hosts, viruses can reshape microbial community structure and drive global nutrient cycling. Over the past decade, viral sequences identified from genomes and metagenomes have provided an unprecedented view of viral genome diver...
Article
Full-text available
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Article
Full-text available
Computer-assisted algorithms have become a mainstay of biomedical applications to improve accuracy and reproducibility of repetitive tasks like manual segmentation and annotation. We propose a novel pipeline for red blood cell detection and counting in thin blood smear microscopy images, named RBCNet, using a dual deep learning architecture. RBCNet...
Conference Paper
Full-text available
The Human Activity Recognition (HAR) is a pattern recognition task that learns to identify human physical activities recorded by different sensor modalities. The application areas include human behavior analysis, ambient assistive living, surveillance-based security, gesture recognition, and context-aware computing. The HAR remains challenging as t...
Conference Paper
In biomedical imaging using video microscopy, understanding large tissue structures at cellular and finer resolution poses many image acquisition challenges including limited field-of-view and tissue dynamics during imaging. Automated mosaicing or stitching of live tissue video microscopy enables the visualization and analysis of subtle morphologic...
Conference Paper
RTip is a tool to quantify plant root growth velocity using high resolution microscopy image sequences at sub-pixel accuracy. The fully automated RTip tracker is designed for high-throughput analysis of plant phenotyping experiments with episodic perturbations. RTip is able to auto-skip past these manual intervention perturbation activity, i.e. whe...
Article
Full-text available
Premise: Aerial imagery from small unmanned aerial vehicle systems is a promising approach for high-throughput phenotyping and precision agriculture. A key requirement for both applications is to create a field-scale mosaic of the aerial imagery sequence so that the same features are in registration, a very challenging problem for crop imagery. M...
Article
Full-text available
Cyber foraging has been shown to be especially effective for augmenting low-power Internet-of-Thing (IoT) devices by offloading video processing tasks to nearby edge/cloud computing servers. Factors such as dynamic network conditions, concurrent user access, and limited resource availability, cause offloading decisions that negatively impact overal...
Article
We introduce a novel discrete cosine transform-based feature (DCTF) descriptor designed for both robustly matching features in aerial video and tracking features across wide-baseline oblique views in aerial wide area motion imagery (WAMI). Our DCTF descriptor preserves local structure more compactly in the frequency domain by utilizing the mathemat...
Conference Paper
Fast, efficient and robust algorithms are needed for real-time visual tracking that could run smoothly onboard airborne embedded systems. In order to efficiently use a motion-detection-based tracking algorithm on a raw image sequence captured by a moving platform, the relative motion between the camera and the ground plane must be stabilized first...
Conference Paper
Visual object tracking has been always an important topic in the computer vision community due to its wide range of applications in many domains. While a considerable number of unsupervised and supervised visual tracking algorithms have been developed, the visual tracking field continues to explore improved algorithms and challenging new applicatio...
Chapter
Geospatial video analytics involves “data collection” of massive image/video data from the Internet of Things (IoT), and “data processing” through seamless computing at the infrastructure edge and core/public cloud platforms. Particularly in cases of (man‐made or natural) disaster incident response coordination scenarios, geospatial video analytics...
Article
Full-text available
Traditionally, Network Function Virtualization uses Service Function Chaining (SFC) to place service functions and chain them with corresponding flows allocation. With the advent of Edge computing and IoT, a reliable orchestration of latency-sensitive SFCs is needed to compose and maintain them in geo-distributed cloud infrastructures. However, the...
Article
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A reliable method to estimate population sizes of wild turkeys (Meleagris gallopavo) using unmanned aerial vehicles and thermal video imaging data collected at several field sites in Texas is described. Automating the data processing of airborne survey videos provides a fast and reproducible way to count wild turkeys for wildlife management and con...
Preprint
The parameter space of CNT forest synthesis is vastand multidimensional, making experimental and/or numericalexploration of the synthesis prohibitive. We propose a morepractical approach to explore the synthesis-process relationshipsof CNT forests using machine learning (ML) algorithms toinfer the underlying complex physical processes. Currently, n...
Chapter
Aerial video captured from an airborne platform has an expanding range of applications including scene understanding, photogrammetry, surveying and mapping, traffic monitoring, bridge and civil infrastructure inspection, architecture and construction, delivery, disaster and emergency response, news and film, precision agriculture, and environmental...
Chapter
Full-text available
The Vision Meets Drone (VisDrone2020) Multiple Object Tracking (MOT) is the third annual UAV MOT tracking evaluation activity organized by the VisDrone team, in conjunction with European Conference on Computer Vision (ECCV 2020). The VisDrone-MOT2020 consists of 79 challenging video sequences, including 56 videos (\(\sim \)24K frames) for training,...
Chapter
Efficient and accurate estimation of homographies among images is the first step in mosaicking crop fields for phenotyping. The current strategy uses sophisticated vehicles that have excellent telemetry to hover over a grid of waypoints, imaging each one. This approach simplifies homography estimation, but precludes more flexible, adaptive protocol...
Article
Regularization methods are used widely in image selective smoothing and edge preserving restoration of noisy images. Traditional methods utilize image gradients within regularization function for controlling the smoothing and can produce artifacts when noise levels are higher. In this work, we consider a robust image adaptive exponent driven regula...
Chapter
The retina is directly connected to the central nervous system and the vascular circulation, which uniquely enables three-dimensional retinal tissue structures and blood flow dynamics to be imaged and visualized from the exterior using non-invasive imaging modalities. Rapid advances in the types of diagnostic imaging modalities, combined with image...
Article
Full-text available
Facial expressions are a significant part of non-verbal communication. Recognizing facial expressions of people with neurological disorders is essential because these people may have lost a significant amount of their verbal communication ability. Such an assessment requires time consuming examination involving medical personnel, which can be quite...
Article
Full-text available
The contribution of cranial dura mater vascular networks, as means for maintaining brain fluid movement and balance, and as the source of significant initiators and/or contributors to neurological disorders, has been overlooked. These networks consist of both blood and lymphatic vessels. The latter were discovered recently and described as sinus-as...
Conference Paper
https://www.semanticscholar.org/paper/Deep-U-Net-Regression-and-Hand-Crafted-Feature-for-Kassim-Glinskii/28b5aff99b2e4472c9de6b90d8896221bfd5c766
Preprint
Full-text available
Detection of moving objects such as vehicles in videos acquired from an airborne camera is very useful for video analytics applications. Using fast low power algorithms for onboard moving object detection would also provide region of interest-based semantic information for scene content aware image compression. This would enable more efficient and...
Chapter
Full-text available
Drones equipped with cameras have been fast deployed to a wide range of applications, such as agriculture, aerial photography, fast delivery, and surveillance. As the core steps in those applications, video object detection and tracking attracts much research effort in recent years. However, the current video object detection and tracking algorithm...
Article
Full-text available
Despite the remarkable progress that has been made to reduce global malaria mortality by 29% in the past 5 years, malaria is still a serious global health problem. Inadequate diagnostics is one of the major obstacles in fighting the disease. An automated system for malaria diagnosis can help to make malaria screening faster and more reliable. We pr...
Conference Paper
Full-text available
Video object tracking has been used with great success in numerous applications ranging from autonomous vehicle navigation to medical image analysis. A broad and emerging domain for exploration is in the field of automatic video-based animal behavior understanding. Interesting, yet difficult-to-test hypotheses, can be evaluated by high-throughput p...