AI Model Protection - FPGA Real-Time AI Model Encryption and Decryption

AI models are vital assets, at risk of leakage, tampering, and unauthorized use during distribution. In collaboration with JmemTek, we have developed a solution that combines encryption and hardware acceleration to protect AI models.

Core Features

• Model Encryption Protection: Encrypts AI model weights and input images to prevent unauthorized access during transmission and storage.
• Real-Time Decryption and Inference: Accelerates decryption and inference using JmemTek’s and our AI hardware IP to meet real-time processing needs.
• Tamper-Proof Validation: Encrypted models include integrity checks to detect unauthorized modifications, ensuring authenticity and accuracy.

Use Cases & Customer Value

• Model Commercialization and Distribution: FPGA-accelerated encryption ensures data security during model distribution.
• Cloud Model Protection: Safeguards model deployment in the cloud with encryption and decryption modules.
• Edge Device Deployment: Enables real-time decryption and efficient inference on edge devices for various applications.

Advanced Driver Assistance System - FPGA Real-Time Image Processing Acceleration

We have developed a high-precision, high-performance, low-latency lane recognition solution using customized development and advanced image processing algorithms.

Core Features

• Hardware Acceleration: FPGA-based parallel processing to improve image computation efficiency.
• Algorithm Optimization: Hardware optimizations for lane recognition and vehicle distance estimation, reducing power and latency.
• Flexible Integration: Supports multiple interfaces (e.g., MIPI, CAN), enabling seamless integration of cameras and sensors.

Use Cases & Customer Value

• Autonomous Vehicles: Lane recognition, vehicle detection, and navigation support for autonomous driving.
• ADAS: Lane departure warning, distance monitoring, and safety features to enhance driving safety.
• Smart Traffic Management: Real-time processing and analysis of dynamic traffic data in smart transportation systems.

Low-Power AI Accelerator - Hardware-Software Co-Design Smart Solution

We have developed a low-power AI accelerator solution through hardware-software co-design, integrating software algorithms with hardware architecture for superior performance and energy efficiency.

Core Features

• Hardware-Software Co-Design: Optimizes hardware during the design phase based on algorithm requirements, ensuring optimal resource allocation.
• Efficient Data Flow Management: Dedicated data path design enhances internal data processing efficiency, reducing power waste.
• Flexible Model Support: Compatible with mainstream deep learning models like CNN and Transformer, meeting diverse application needs.

Use Cases & Customer Value

• Smart Devices: Provides efficient AI inference for smart home and edge computing devices.
• Smart Healthcare: Real-time AI analysis for portable diagnostic equipment, enhancing medical efficiency.
• Industrial Automation: Supports low-power computing for industrial inspection and predictive maintenance, handling large-scale data processing.