54 skills found · Page 1 of 2
zjunlp / DeepKE[EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and Construction
Faceplugin-ltd / FaceRecognition AndroidFace Recognition, Face Liveness Detection, Face Anti-Spoofing, Face Detection, Face Landmarks, Face Compare, Face Matching, Face Pose, Face Expression, Face Attributes, Face Templates Extraction, Face Landmarks
VikasSukhija / DownloadsAD Health Check, Send HTML Email, Ping machines, Encrypt Password,Bulk Password,Microsoft Teams,Monitor Certificate expiry, Monitor cert expiry, AD attributes, IP to Hostname, Export AD group, CSV to SQL,Shutdown, Restart, Local Admin, Disk Space, Account expiry,Restore Permissions, Backup permissions, Delete Files Older Than X-Days, export DHCP options,Read Registry,Distribution group AD attributes,Monitor Windows Services,Export Reverse DNS,Task Monitor,Monitor and alert, Exchange Health check,Get Network Info, Export AD Attributes,AD group members, Office 365 Group member, SQL to CSV, Outlook save send attachments, Upload files to FTP,Exchange – Total Messages Sent Received, Set Teams Only Mode, Intune Duplicate Device,Intune Cleanup Not Evaluated, Ownership and Grant Permissions, Write Create Modify Registry , Organization Hierarchy from AD,Azure AD Privileged Identity Management,Intune – Export MAM Devices,Intune Marking devices as Corporate, Dynamic to Static Distribution Group,Monitor Alert Office 365 services,Group Member Count,Bulk Addition external users sharepoint, ADD to Exchange online License Group,All in One Office 365 Powershell,Bulk Addition of Secondary Email, Automate move mailboxes to o365, Addition Modification Termination Exchange users, Monitoring Unified Messaging port,Unified Messaging Extensions Report, Set Default Quota for SharePoint,Bulk Contact Creation and Forwarding, Uploading and Downloading files sftp, Monitoring Sftp file and download, Office 365 groups Write back, CSV parser, Email address update, Email address modify, MDM enrollment, Welcome Email, Intune Welcome Email, remove messages, remove email, SKOB to AD, SKOB to group, PowerApps report, Powerautomate Report, Flow report, Server QA, Server Check List, O365 IP range, IP range Monitor, o365 Admin Roles, memberof extraction, CSV to Excel, Skype Policy, UPN Flip, Rooms Report, License Reconciliation,Intune Bulk Device Removal, Device Removal, Clear Activesync, Lync Account Termination,Lync Account Removal, Enable office 365 services, Enable o365 Services, Export PST, Site collection Report, Office 365 Group Sites, System Admin,ActiveSync Report,White Space,Active Directory attributes, outlook automation, Intune Detect App, Distribution list Fix, Legacy DN, start service, stop service, disable service, Message tracking, Distribution lists report,Distribution groups report,Quota Report, Auto reply, out of office, robocopy multi session, Home Folder, local admin, Database, UPN SIP Mismatch, Recoverable deleted, teams number, Number assignment, teams phone, AD Group Hierarchy, Hierarchy membership, Sync Groups, Powerapps, Powerapps DLP, AzureAD application, Azure AD Secret, AzureAD Certificate, AzureAD Cert, Powerapps DLP, Download SPO file, Download Sharepoint file, Sharepoint item download
sakuranew / BERT AttributeExtractionUSING BERT FOR Attribute Extraction in KnowledgeGraph. fine-tuning and feature extraction. 使用基于bert的微调和特征提取方法来进行知识图谱百度百科人物词条属性抽取。
google-research-datasets / MAVEThe dataset contains 3 million attribute-value annotations across 1257 unique categories on 2.2 million cleaned Amazon product profiles. It is a large, multi-sourced, diverse dataset for product attribute extraction study.
weblineindia / AIML Human Attributes Detection With Facial Feature ExtractionThis is a Human Attributes Detection program with facial features extraction. It detects facial coordinates using FaceNet model and uses MXNet facial attribute extraction model for extracting 40 types of facial attributes. This solution also detects Emotion, Age and Gender along with facial attributes.
hackerxiaobai / OpenTag 2019Scaling Up Open Tagging from Tens to Thousands: Comprehension Empowered Attribute Value Extraction from Product Title
lonePatient / BERT Attribute Value ExtractA Pytorch implementation of "Scaling Up Open Tagging from Tens to Thousands: Comprehension Empowered Attribute Value Extraction from Product Title" (ACL 2019).
dinobby / ZS BERTOfficial implementation of the paper "Towards Zero-Shot Relation Extraction with Attribute Representation Learning."
daviden1013 / Llm IeA comprehensive toolkit that provides building blocks for LLM-based named entity recognition, attribute extraction, and relation extraction pipelines.
dsabarinathan / Facial Attribute Recognition From Face ImagesFacialAttributesExtractor is a Python library for precise facial attribute extraction, offering comprehensive insights into various features using OpenCV and Deep Learning. Enhance your image processing and real-time video applications with accurate analysis of age, gender, hair length, and more.
MurtuzaBohra / SimpDOMSimplified DOM Trees for Transferable Attribute Extraction from the Web
lumiqai / UOI 1806.01264Unofficial implementation of the paper "OpenTag: Open Attribute Value Extraction from Product Profiles"
mhilmiasyrofi / Product Attribute ExtractionProduct Attributes Extraction in Indonesian e-Commerce Platform
wbsg-uni-mannheim / ExtractGPTAttribute Value Extraction using Large Language Models
Faceplugin-ltd / FaceRecognition FlutterFace Recognition, Face Liveness Detection, Face Anti-Spoofing, Face Detection, Face Landmarks, Face Compare, Face Matching, Face Pose, Face Expression, Face Attributes, Face Templates Extraction, Face Landmarks
jw-07 / ASC ExtractionEfficient Attributed Scattering Center Extraction Using Gradient-Based Optimization in Deep Learning Framworks
bhaveshjaggi / PestDetectionPEST DETECTION USING IMAGE PROCESSING e The principal idea which empowered us to work on the project PEST DETECTION USING IMAGE PROCESSING is to ensure improved and better farming techniques for farmers. Our Solution: The techniques of image analysis are extensively applied to agricultural science, and it provides maximum protection to crops and also much less use of pesticides which can ultimately lead to better crop management and production. The following softwares are required for the project: OpenCV with C++/Python : It is a library which is designed for computational efficiency with a strong focus on real time applications. Pest Detection System Following are the image processing steps which are used in the proposed system. >Color Image to Gray Image Conversion Therefore, images are converted into gray scale images so that they can be handled easily and require less storage. The following equation shows how images are converted into gray scale images. I(x,y)=0.2989*B +0.5870*G +0.1140*B > Image Filtering The PSNR value is calculated for both the average and median resulting images .The average filter provides better result as compared to the median filter. So this paper uses average filter for further processing. > Image Segmentation To detect the pests from the images, the image background is calculated using morphological operators which is most critical after this image is subtracted from the original image. So the resulting image will only have the objects with pixel values 1 and background pixel values 0. >Noise Removal Noise contains dew drops, dust and other visible parts of leaves. As only the object of interest was to be visible on the images,so the aim was to remove the noise to get better and effective results. The Erosion algorithm has been used to remove isolated noisy pixels and to smoothen object boundaries . After noise removal,the next goal was to enhance the detected pests after segmentation which was performed by using the dilation algorithm. >Feature Extraction Different properties of the images are calculated on the basis of those attributes using which image is classified. For image properties, gray level co-occurrence matrix and regional properties of the images are calculated. These properties are used to train the support vector machine to classify images. >Counting of the pests on the leaves is the main purpose, so that it can give an idea of how much pests are there on a leaf.It uses Moore neighborhood tracing algorithm and Jacob's stopping criterion Feasibility: The present framework of pest detection is quite tedious and laborious for the farmers as they have to carry out their acre-acres surveys themselves and it requires a lot of vigorous efforts to achieve the same.Image analysis provides a realistic opportunity for the automation of insect pest detection.Through this system, crop technicians can easily count the pests from the collected specimens, and right pests’ management can be applied to increase both the quantity and quality of production. Using the automated system, crop technicians can make the monitoring process easier. So in order to bring enhancements in the system,we came up with more productive and well organised system with our idea .Due to this automaton applied,lucrativeness increases and labour is reduced.
HenryPengZou / ImplicitAVE[ACL 2024] Dataset and Code of "ImplicitAVE: An Open-Source Dataset and Multimodal LLMs Benchmark for Implicit Attribute Value Extraction"
wbsg-uni-mannheim / Wdc PaveWeb Data Commons - Using LLMs for Product Attribute Value Extraction and Normalization
