| Model Type | Image Classification |
|---|---|
| Framework | AI Edge LiteRT, OpenVINO |
| Algorithm | ShuffleNet v2 |
| Technical Details | Classifies images into predefined visual categories for real-time vision and edge applications. |
Image Classification
Real-time image classification for recognizing visual categories on edge devices.
Leave your message here
Fill the form with the required information
$0.00
Image Classification
app details
Resources
Use Cases
Quality Control
Supported SECO Devices
AI optimized hardware
Fanless embedded PCs
Modules
supported chipsets
Intel® Core™ i3
Qualcomm® Dragonwing QCS6490
Qualcomm® Dragonwing QCS5430
NXP i.MX 8M Plus
NXP i.MX 95
Performance Benchmark
Hardware · Backend
Processing unit
Latency (ms)
Avg. Peak RAM
Intel Tiger Lake · OpenVINO
GPU
5.2 ms
526 MB
Intel Tiger Lake · OpenVINO
CPU
1.9 ms
523.3 MB
Intel Tiger Lake · AiEdgeLiteRT
CPU
1.9 ms
83.4 MB
MediaTek Genio 510 · AiEdgeLiteRT
CPU
11.4 ms
78 MB
NXP i.MX 8M Plus · AiEdgeLiteRT
NPU
12.7 ms
76.1 MB
NXP i.MX 8M Plus · AiEdgeLiteRT
GPU
12.7 ms
76.1 MB
NXP i.MX 8M Plus · AiEdgeLiteRT
CPU
22.1 ms
76.1 MB
Qualcomm QCS6490 · AiEdgeLiteRT
NPU
1.2 ms
80.4 MB
Qualcomm QCS6490 · AiEdgeLiteRT
CPU
10.9 ms
79.8 MB
Object Detection – YOLOX
Detects and locates multiple object categories in images and video streams using the lightweight YOLOX architecture.
View Model
Automated Quality Inspection with Vision AI
Real-time AI-powered vision system for detecting defects in manufacturing environments
View Model
YAMNet for Environmental Sound Classification
Real-time environmental sound classifier optimized for low-power edge devices using MobileNet v1.
View Model
Semantic Segmentation
Real-time semantic segmentation for understanding roads, vehicles, pedestrians, and other elements in visual scenes.
View Model|
|