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DiPLIP: Distributed Parallel Processing Platform for Stream Image Processing Based on Deep Learning Model Inference
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-11021-5_35openalex-snapshot
Real-Time Dynamic Object Detection for Autonomous Driving Using Prior 3D-Maps
inferredcites →https://doi.org/10.1007/978-3-030-11723-8_28openalex-snapshot
Multi-scale Deep Convolutional Neural Network for Stroke Lesions Segmentation on CT Images
inferredcites →https://doi.org/10.1007/978-3-319-10602-1_48openalex-snapshot
Microsoft COCO: Common Objects in Context
inferredcites →https://doi.org/10.1007/978-3-319-46448-0_2openalex-snapshot
SSD: Single Shot MultiBox Detector
inferredcites →https://doi.org/10.1007/978-3-319-54193-8_13openalex-snapshot
End-to-End Training of Object Class Detectors for Mean Average Precision
inferredcites →https://doi.org/10.1109/cvpr.2016.91openalex-snapshot
You Only Look Once: Unified, Real-Time Object Detection
inferredcites →https://doi.org/10.1109/mcc.2014.22openalex-snapshot
Streaming Big Data Processing in Datacenter Clouds
inferredcites →https://doi.org/10.1109/tpami.2016.2577031openalex-snapshot
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
inferredcites →https://doi.org/10.1109/vtdc.2006.17openalex-snapshot
Virtual Machine Hosting for Networked Clusters: Building the Foundations for "Autonomic" Orchestration
inferredcites →https://doi.org/10.1145/1107499.1107504openalex-snapshot
The 8 requirements of real-time stream processing
inferredcites →https://doi.org/10.1186/s13640-018-0279-5openalex-snapshot
RIDE: real-time massive image processing platform on distributed environment
inferredcites →https://doi.org/10.3390/computers3040117openalex-snapshot
Beyond Batch Processing: Towards Real-Time and Streaming Big Data
inferredcites →https://doi.org/10.5555/1972457.1972488openalex-snapshot
Mesos: a platform for fine-grained resource sharing in the data center
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-031-25088-0_41openalex-snapshot
Application of a Novel Deep Learning Model to Recognize and Predict Kidney Disease in the Context of Image Processing
inferred← citeshttps://doi.org/10.1007/978-3-031-63139-9_7openalex-snapshot
Research on Piano Harmony Automatic Orchestration System Based on Deep Learning
inferred← citeshttps://doi.org/10.1109/icpcsn62568.2024.00017openalex-snapshot
Enhancing Chronic Kidney Disease Diagnosis Through Densenet-121 Approach
inferred← citeshttps://doi.org/10.1109/icses60034.2023.10465442openalex-snapshot
Deep Learning Technique to Detect and Diagnose the Anomalous in Kidney
inferred← citeshttps://doi.org/10.1109/ismsit52890.2021.9604746openalex-snapshot
A Survey of Publish/Subscribe Middleware Systems for Microservice Communication
inferred← citeshttps://doi.org/10.1109/ojcoms.2026.3679492openalex-snapshot
Delay-Aware Multi-Stage Edge Server Upgrade With Budget Constraint
inferred← citeshttps://doi.org/10.3390/app13063621openalex-snapshot
A Deep Learning Approach for Kidney Disease Recognition and Prediction through Image Processing
inferred← citeshttps://doi.org/10.3390/electronics10222878openalex-snapshot
Machine Learning and Fuzzy Logic in Electronics: Applying Intelligence in Practice
inferred← citeshttps://doi.org/10.4018/ijitsa.324761openalex-snapshot
Design of Graphic Design Assistant System Based on Artificial Intelligence
inferred← citeshttps://doi.org/10.47992/ijmts.2581.6012.0367openalex-snapshot
Advancing Healthcare: Integrating A Deep Neural Network With The Bio-Inspired Puffer Fish Optimization Algorithm For Early Detection And Prediction Of Chronic Kidney Disease
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