Real-time
Computer Vision & Ai
Accurate Image processing and Video processing depends on multitude of factors. At EMVOKE build your own custom model or ensemble of models for Image Processing. As image / video processing is based on Image / Video quality , type of image , lighting, occlusion, noise and various other factors we ensure the optimal choice of algorithms are fitted for best performance.
Do Object detection, tracking, image segmentation, near real-time video analysis using various algorithms,
Ex: Open CV based ML - Feature engineering, Nano-nets, Yolo, Transformer Networks, GANS, SEER, Faster, R-CNN, U-Nets, Single Shot Learning and many more. Run your algorithms on the edge or on the Server side.
#End to End Computer Vision Pipeline
Train: Train your Computer - Vision Model (Image/Video) for Edge Detection or On-Server.
Ingest: Ingest Video & Images @scale, in various formats from multiple Sources.
Frame Processing: Frame processing using ffMpeg, gStreamer.
Stream: Stream & Store Data - Real-time & Near Real-time.
Detection with Ai : Classify Objects, Scene & Context on Image / Video.
Act: Notify Detection & Push Decision flow as required.
#EMVOKE AI USP
Multi Model
Parallelized training
Multi Algorithms (Ensambles)
Models for Sparse & Big Data
Scale for Value
Real-time Ai Model prediction
Model and Ai pipeline optimization @ Scale
Cost Optimization
Weights & Pipeline Aligned to OPEX
Transfer learning 4 quick adoption.
Synthetic Data Generation.
Advanced Tuning
Hyper-parameter Tuning with
Random search
Weight Pruning
Parameter Tools & More..
#Computer Vision as a service
Object Detection
There are several Text Classification algorithms that are key for Intent Classification to Context analysis. Now get your data trained and classified to invoke real-time decision making and to gain insights.
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At EMVOKE based on Data size, type of data, scale & speed get your Model trained for optimal performance and cost. Be it using basic ML techniques like SVM, Naive Bayes to using Advanced Deep Neural Networks like, Bi-LSTM, Bert, Transformer Networks etc. We train models both from the scratch or by applying transfer learning as per need.
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Get End to End NLP Model as a service for both Edge and On-Server solutions.
#Vision Use-cases
Object Detection
Multi-Object classification.
Object Tracking.
Shelf Classification.
& More...
#Live Stream Object Tracking
Live Streaming ML & Ai Models on any real-time media steam is a very complex task where-in real-time feedback is needed with object detection and tracking per frame, often scale, compute costs and edge deployment memory footprint are major bottle-necks. We use various models, example - Ensemble networks, Encoder-Decoder models, Deep-sort, SORT, Kalman filters etc with Weight optimization techniques, to improve Model accuracy, Model Scale and reduce Cost run-downs.
#Error Detection
Detect Fault lines & Cracks.
Identify Manufacturing Defects.
Select Models- Deep Nets & Open CV-ML.
Optimize Models for Scale.
#Bounding Box to Polygons
Multi-object classification.
Instance & Semantic segmentation.
Synthetic Image generation.
#Medical Image processing
Accurate Image model tuned to pixel level.
Detect ROI in image scans.
De-noise data and avoid overlaps.
Use of both Classification & Clustering.
Run Models on Edge & Server.
PII, Secure & GDPR Compliant.
