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RV1103G1 RV1103 highly integrated vision processor SoC IC for IPC for AI application

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Product Description

📊 Basic Information
Model NO.
RV1103G1
Operating Temp.
-55℃ - 125℃
MFR.
ROCKCHIP
D/C
23+
Package
QFN88
Quality
Genuine New Original
Product Status
Active
Production Capacity
1000000PCS
📦 Packaging & Delivery
Package Size
20.00cm * 20.00cm * 5.00cm
Gross Weight
0.500kg
📝 Product Description

RV1103G1: Highly integrated vision processor SoC for IPC, especially designed for AI-related applications. Based on a single-core ARM Cortex-A7 32-bit core integrating NEON and FPU.

Key Features:
- Build-in NPU supporting INT4/INT8/INT16 hybrid operations (up to 0.5TOPs).
- Hardware-based 4-Megapixel ISP with HDR, 3A, 3DNR, and dehaze.
- Supports H.265/H.264 multi-stream encoding.
- Integrated 16-bit DRAM DDR2 and audio codec.

CategoryEmbedded Processors & Controllers/Microcontrollers (MCU/MPU/SOC)
ManufacturerRockchip
PackageQFN-88(9x9)
Quality100% Original
WarrantyONE YEAR
🖼️ Product Visuals
📜 Certificates & Quality
⭐ Why Choose This Solution
  • 100% guarantee components quality: Genuine Original.
  • Sufficient stock for urgent demands.
  • Sophisticated technical support to reduce manufacturing risks.
  • Faster shipment: In-stock components can ship the same day.
  • 24 Hours service availability.
❓ FAQ
Q1: Is the RV1103G1 vision processor original?
A: Yes, we guarantee 100% Genuine New Original quality for all components.
Q2: What is the computing power of the integrated NPU?
A: The build-in NPU supports INT4/INT8/INT16 hybrid operations with computing power up to 0.5TOPs.
Q3: Does it support H.265 encoding?
A: Yes, the embedded video encoder supports both H.265 and H.264 encoding with multi-stream capabilities.
Q4: What is the warranty period for this IC?
A: The product comes with a standard ONE YEAR warranty.
Q5: How quickly can the product be shipped?
A: For components in stock, we can arrange shipment on the same day.
Q6: Which frameworks are compatible with the NPU?
A: It is compatible with TensorFlow, MXNet, PyTorch, and Caffe frameworks.

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