Advanced driver-assistance systems powered by deep learning models are transforming the mobility and transportation industry. However, a common barrier to deployment is the inability to achieve high accuracy and real-time inference performance on edge devices. Both factors are absolutely mission critical for ensuring not only the application’s usability, but also safety for the users.
Watch a compilation of clips demonstrating how you can use Deci to develop a variety of automotive use cases.
An automotive company running a U-Net based segmentation model on a NVIDIA Jetson Xavier NX struggled to achieve the target latency in production.
Using Deci’s AutoNAC engine, a faster and smaller model was generated. Latency was reduced by 2.1x, model size was reduced by 3x, and memory footprint was reduced by 3x – all while maintaining the original accuracy.
Deci is used by companies in the automotive industry to develop and optimize a wide range of applications. Here are some examples.
Advanced Driver Assistance Systems
Pothole Detection
Automatic Number Plate Recognition
Occupant Monitoring System
Parking Monitoring
Automotive Manufacturing
The Deci platform is used by data scientists and machine learning engineers to build, optimize, and deploy highly accurate and efficient models to production. Teams can easily develop production grade models and gain unparalleled accuracy and speed tailored for any performance targets and hardware environment. Deci is powered by AutoNAC (Automated Neural Architecture Construction), the most advanced and commercially scalable Neural Architecture Search engine in the market. AutoNAC performs a multi-constraints search to find the architecture that delivers the highest accuracy for any performance targets and hardware environment.
Build accurate & efficient architectures tailored to your hardware and application’s performance targets with Deci’s Neural Architecture Search engine.
Easily compile and quantize your models (FP16/INT8) and evaluate different production settings with a click of a button.
Train models with SuperGradients. Leverage custom recipes and advanced training techniques (e.g. knowledge distillation, quantization-aware training) with one line of code.
Deploy your models with Infery, Deci’s simple-to-use, unified, model inference API. Streamline deployment and boost serving performance with parallelism and concurrent execution. Compatible with multiple frameworks and hardware.
Deci is ISO 27001
Certified
from transformers import AutoFeatureExtractor, AutoModelForImageClassification
extractor = AutoFeatureExtractor.from_pretrained("microsoft/resnet-50")
model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-50")