Chana O.

Responsibilities:

• Deep Learning Pipeline Development Developed an end-to-end inference pipeline using PyTorch → ONNX → TensorRT, integrated with NVIDIA DeepStream and GStreamer for real-time video processing and classification.

• GPU Optimization & C++ Integration Implemented high-performance C++ modules with CUDA acceleration, achieving 31% performance improvement (120ms → 83ms for ResNet18). Created Python bindings using Pybind11 for seamless integration.

• Computer Vision Algorithms Developed advanced image processing algorithms including ExG (Excess Green) background removal, Otsu thresholding, and morphological operations for improved plant detection accuracy.

• Real-time Video Processing Built GStreamer-based video pipelines with RTSP streaming support, enabling real-time frame processing and intelligent frame skipping based on content analysis.

• Edge Computing Deployment Optimized the system for NVIDIA Jetson platforms with ARM64 compilation, TensorRT optimization, and efficient memory management for field deployment.

• Build System & DevOps Created advanced Makefile-based build system supporting CUDA 12.2, cross-compilation for ARM64, and automated d

• Build System & DevOps Created advanced Makefile-based build system supporting CUDA 12.2, cross-compilation for ARM64, and automated dependency management for multiple target platforms.

• Memory Management Optimization Implemented zero-copy memory management with direct EGL-CUDA interoperability, eliminating unnecessary data transfers between GPU and CPU memory spaces.

• System Integration & Testing Integrated all components into a cohesive system with comprehensive error handling, logging, and performance monitoring for production deployment.