Search Results for "leaf disease detection"
Sort By:
Showing 21 open source projects for "leaf disease detection"
View related business solutions-
Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
-
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
1
HealthFusion
AI Disease Detections System
HealthFusion has identified a critical business problem, which is the lack of accessibility and timely detection of multiple diseases. The traditional approach of detecting diseases is time-consuming, expensive, and not accessible to everyone, especially in remote areas. This problem can lead to delayed diagnosis and treatment, which can have serious consequences for patients. The proposed solution, HealthFusion, is novel and practical as it offers a comprehensive solution to detect... -
2
-
3
W2MHS-DNN
Open Source White Matter Hyperintensities Segmentation Toolbox
Wisconsin White Matter Hyperintensity Segmentation [W2MHS] and Quantification Toolbox is an open source MatLab toolbox designed for detecting and quantifying White Matter Hyperintensities (WMH) in Alzheimer’s and aging related neurological disorders. WMHs arise as bright regions on T2- weighted FLAIR images. They reflect comorbid neural injury or cerebral vascular disease burden. Their precise detection is of interest in Alzheimer’s disease (AD) with regard to its prognosis. Our toolbox provides a self-sufficient set of tools for segmenting these WMHs reliably and further quantifying their burden for down-processing studies. -
4
Nuvarator
A SNV Detection Software Tools Installer Package
A software package Nuvarator which downloads and installs different tools related to Somatic SNV detection. SNV detection is range of computational tech- niques and algorithms used to identify the existence of single nu- cleotide variants (SNVs) by using the result from Next Generation Sequencing (NGS) experiments. NGS are methods employed for Whole Genome Sequencing, a process for determining the precise order of nucleotides within a DNA molecule which can improve the knowledge available to researchers interested in evolutionary biology, and hence lays the foundation for predicting disease susceptibility and drug response. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
5
ISVASE
identification of sequence variant associated with splicing event
To generate correct mature mRNAs, the exons must be identified and joined together precisely and efficiently by RNA splicing mechanism. It is to be noted that about one third or a half of all disease-causing mutations effect RNA splicing. However, there is little bioinformatics tools to directly identify sequence variants associated with splicing events (SVASE) based on RNA-seq data. We developed ISVASE, a simple and convenient tool for identifying SVASE directly using RNA-seq data. Comparing with the existing software PVAAS, our method has several advantages such as stringent rule-depended filters and statistical filters in each step, detection sequence variants for known splicing events, identification sequence variants in two parts of splicing (junction) separately, detection junction shift events if providing known splicing annotation, evaluating splicing signal, comparing with known DNA mutation and/or RNA editing data, and short running time. -
6
MetaOpen
Metabolomics Bioinformatics Tools
...Each type of analysis affords limited analyte coverage of molecules present in a patient sample and therefore provides only a partial molecular profile for an individual patient. These diverse analytical data must be integrated with advanced bioinformatics methods for accurate evaluation of health and detection of disease susceptibility. -
7
Plant Leaf Detection
Automated counting and labelling of rosette plant leaves
-
8
Featureextraction
Feature Extraction: Fractal, Statistical, Geostatistical, Succolarity
The objective of this project is to find in the literature the best feature extractors related to the detection and diagnosis of disease in the breast, and implement them in order to make it open to research groups worldwide. The features will be available as an API (Application Programming Interface) in Java. -
9
ExAM-Exome_Analysis_And_Mining
A whole exome sequencing analysis package and its graphical interface
...Here, we present an interactive and free analysis package, ExAM, dedicated to whole exome sequencing data analysis. It is accessible to non-computer scientists and provides a complete set of information, as well as decision support to prioritize candidate disease causing variants. -
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
-
10
Virmid
Virtual Microdissection for SNP calling
NEWS: 11-07-2013 A new version Virmid 1.1.0 has been uploaded. 08-29-2013 Virmid paper is now published in Genome Biology. Kim S et al, "Virmid: accurate detection of somatic mutations with sample impurity inference", Genome Biology 2013, 14:R90 http://genomebiology.com/2013/14/8/R90/abstract Virmid (Virtual Microdissection for SNP calling) is a Java based variant caller designed for disease-control matched samples. Virmid is also specialized for identifying potential within individual contamination where the disease sample cannot be purified enough. ... -
11
SEM_bestShortestPath
A SEM-based method for disease module detection
SEM_bestShortestPath is a Structural Equation Modeling (SEM)-based methodology to evaluate the most important shortest paths between differentially expressed genes in biological interaction networks, with absolutely no need of user-defined parameters or heuristic rules, enabling a free-of-bias discovery and overcoming common issues affecting recent network-based algorithms. SEM-bsp is based on Structural Equation Modeling techniques to detect significantly perturbed sub-networks (disease... -
12
HomSI
Homozygous Stretch Identifier from next-generation sequencing data
...This situation leads to the prevalence of recessive diseases among the members of these families. Homozygosity mapping is based on this observation and several recessive disease genes have been discovered with the help of this technique in consanguineous families. The researchers typically use SNP arrays to determine the homozygous regions and then search for the disease gene by sequencing the genes within this candidate disease loci. Recently, the advent of next generation sequencing enables the concurrent identification of homozygous regions and the detection of mutations relevant for diagnosis, using data from a single sequencing experiment. ... -
13
VarImpact
Extracting effects of mutations on molecular properties from text.
...Our aim is to bridge the gap between detection of genetic variants and their annotation with aforementioned observations. VarImpact extracts experimentally observed changes from the literature. This allows to annotate sequencing results with observed impacts, gather information about the mutational landscape observed in disease populations, and to study disease mechanisms. -
14
PathNER
A tool for systematic identification of biological pathway mentions
PathNER is a tool for the identification of specific pathway mentions from biomedical literature. PathNER is built upon the GATE embedded framework.It's based on soft dictionary matching and rules-based detection. The dictionary is generated from ConsensusPathDB and Pathway Ontology and the rules are implemented in JAPE. Using PathNER, you can identify all occurrences of informative pathway names (e.g. 'the Wnt pathway'). PathNER can be used to assist studies that aim at uncovering associations between disease and pathways. The latest updates will be on GitHub : https://github.com/chengkun-wu/PathNER -
15
WM Hyperintensities Segmentation Toolbox
Open Source White Matter Hyperintensities Segmentation Toolbox
Wisconsin White Matter Hyperintensity Segmentation [W2MHS] and Quantification Toolbox is an open source MatLab toolbox designed for detecting and quantifying White Matter Hyperintensities (WMH) in Alzheimer’s and aging related neurological disorders. WMHs arise as bright regions on T2- weighted FLAIR images. They reflect comorbid neural injury or cerebral vascular disease burden. Their precise detection is of interest in Alzheimer’s disease (AD) with regard to its prognosis. Our toolbox provides a self-sufficient set of tools for segmenting these WMHs reliably and further quantifying their burden for down-processing studies. -
16
RODS (Real-time Outbreak and Disease Surveillance) is a real-time computer-based public health surveillance system initially developed at the RODS Laboratory, University of Pittsburgh for the early detection of disease outbreaks .
-
17
PathMEN
A Java tool for mining pathway mentions from literature
PathNER is a tool for the identification of specific pathway mentions from biomedical literature. PathNER is built upon the GATE embedded framework.It's based on soft dictionary matching and rules-based detection. The dictionary is generated from ConsensusPathDB and Pathway Ontology and the rules are implemented in JAPE. Using PathNER, you can identify all occurrences of informative pathway names (e.g. 'the Wnt pathway'). PathNER can be used to assist studies that aim at uncovering associations between disease and pathways. -
18
MetCore
Metabolomics Bioinformatics Tools
...Each type of analysis affords limited analyte coverage of molecules present in a patient sample and therefore provides only a partial molecular profile for an individual patient. These diverse analytical data must be integrated with advanced bioinformatics methods for accurate evaluation of health and detection of disease susceptibility. -
19
BayesianCortex
simple algorithm for a realtime interactive visual cortex for painting
A paint program where the canvas is the visual cortex of a simple kind of artificial intelligence. You paint with the mouse into its dreams and it responds by changing what you painted gradually. There will also be an API for using it with other programs as a general high-dimensional space. Each pixel's brightness is its own dimension. Bayesian nodes have exactly 3 childs because that is all thats needed to do NAND in a fuzzy way as Bayes' Rule which is NAND at certain extremes. NAND can be... -
20
Foad is an open source software which receive an EKG Signal from scanner, WFDB database or heart sensors. Finding patient disease started by taking Fourier transform (FFT) from input signal and extract a single cycle. Based on some heuristic algorithm the most important feature like P , Q , R , S , T captured and feed to trained neural network. and so the final decision made by CNN library. As mentioned before this software also capable do some image processing on scanned paper to lower...
-
21
Medical Datasets (In a text file, with space separated values) can be loaded to the system. By choosing either one of the two classifiers, Neural network or Decision Tree, the system can be trained and evaluated.
- Previous
- You're on page 1
- Next
