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English
$
USD
I will build state of the art multi object detection projects
Ab Qyum
About this gig
My Intro:
Have 6+ years of with experience in AI-driven projects ,Backend development and Deployment the AI model. I am passionate about building scalable AI solutions.I thrive on solving complex problems and optimizing AI systems for real-world applications..Interviewed at FAANG company for multiples time.
Project Description:
IT contains a state-of-the-art multi-object project for segmentation, object detection on Nvidia Jetson Nano and show performance difference between yolov8 VS yolov11 model according to FPS
Provided Services:
- multi-object project for segmentation, object detection and object tracking
Used :
- yolo
- twensorflow
- FastAPI
- bitbucket
Tracking method :
botsort
deepocsort
strongsort
ocsort
bytetrack
Get to know Ab Qyum
Ab Qyum
Staff AI Engineer
- FromBangladesh
- Member sinceOct 2022
- Last delivery1 year
Languages
Bengali, English
Hello,
Have 6+ years of with experience in AI-driven projects ,Backend development and Deployment the AI model. I am passionate about building scalable AI solutions.I thrive on solving complex problems and optimizing AI systems for real-world applications.
*Languages :Python,C/C++.
*Services:
EDA,Deepfake detection ,Recommender System,Audio/Speech Recognition ,Face verification and Recognition ,anomaly/Fraud detection and Segmentation ,Generative AI model,RAG and Langchain etc
•Tools : Git,Github,Bitbucket,GCP.
•Accelerators :GPU,TPU.
Portfolio: https://portfolio-aumk.onrender.com/
FAQ
What is object detection?
Object detection is a computer vision technique that identifies and locates objects within an image or video.
What are common applications of object detection?
Applications include autonomous vehicles, security surveillance, medical imaging, retail analytics, and industrial automation.
What are popular object detection models?
Common models include YOLO (You Only Look Once), SSD (Single Shot MultiBox Detector), and Faster R-CNN.
How does object detection differ from image classification?
Image classification labels an entire image, while object detection identifies and locates multiple objects within an image.
What are challenges in object detection?
Challenges include occlusion, lighting variations, real-time processing, and detecting small or overlapping objects.
