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Burak Ercan
Verified Expert in Engineering
Computer Vision Developer
Ankara, Turkey
Toptal member since September 27, 2022
Bio
Burak is a senior computer vision/AI engineer with a PhD and 15 years of industrial experience. As an expert in computer vision, deep learning, and software development with C++ and Python, he's worked on various projects in large defense companies and AI startups, demonstrating a broad range of technical and soft skills. Burak describes himself as a lifelong learner. His goal is to be a part of impactful applied research and engineering where he can fully demonstrate his skills.
Portfolio
Freelance Client
C++, Real-time Operating System (RTOS), NVIDIA CUDA, NVIDIA Jetson...
Exin Health AI
Python, Computer Vision, Audio Processing, Speech-to-Text (STT)...
HAVELSAN
C++, Python, PyTorch, OpenCV, Robot Operating System (ROS), GStreamer, PCL...
Experience
- C++ - 11 years
- Python - 7 years
- PyTorch - 7 years
- NVIDIA Jetson - 5 years
- Computer Vision - 5 years
- Deep Learning - 4 years
- NVIDIA Triton - 3 years
- Large Language Models (LLMs) - 1 year
Work Experience
Principal Computer Vision & Embedded AI Engineer
2025 - 2026
Freelance Client
- Utilized NVIDIA Nsight to profile and re-implemented an image-processing pipeline on Jetson Orin Nano using NVIDIA Performance Primitives (NPP), achieving 6× higher performance than OpenCV CPU and 3× higher performance than OpenCV CUDA streams.
- Applied real-time Linux techniques (CPU isolation, affinity, interrupt routing, RT scheduling) on Jetson Orin Nano to stabilize critical paths, reducing timing variability by up to 8× (MSE) for latency-sensitive events.
- Designed and implemented custom color-conversion routines supporting multiple bit depths, color spaces, and pixel formats, then optimized them using thread-level parallelism and CPU SIMD intrinsics, resulting in a 20× reduction in runtime.
- Led technical direction and architecture decisions while maintaining hands-on ownership of the entire embedded AI pipeline and core development.
Technologies: C++, Real-time Operating System (RTOS), NVIDIA CUDA, NVIDIA Jetson, Object Detection, Embedded Linux, OpenCV, Video Processing, Image Processing, Deep Learning, SIMD, Parallel Programming, You Only Look Once (YOLO), Open Neural Network Exchange (ONNX), Embedded Systems, Edge AI, ONNX Runtime, Real-time Embedded Systems, Video & Audio Processing, FFmpeg, GPGPU, GPU Computing, Graphics Processing Unit (GPU), Low-latency Software, NVIDIA Jetson AGX Orin, User Interface (UI), Real-time Systems, Edge Computing
Staff Machine Learning Engineer
2024 - 2025
Exin Health AI
- Designed and developed various AI-driven solutions for improving efficiency and safety in operating rooms.
- Developed algorithms with various computer vision tasks such as classification, object detection, instance segmentation, and temporal action localization.
- Developed an end-to-end federated learning pipeline with components for servers, clients, data gathering and annotation, performance assessment, etc.
- Handled audio processing pipelines, including voice activity detection and speech recognition.
- Contributed to large language models (LLMs) for extracting information from noisy automatic speech recognition (speech-to-text) outputs.
- Developed complex algorithms and data-flow pipelines with components spanning edge devices, cloud platforms, and local workstations.
Technologies: Python, Computer Vision, Audio Processing, Speech-to-Text (STT), Speech Recognition, Automatic Speech Recognition (ASR), Natural Language Processing (NLP), Large Language Models (LLMs), Object Detection, Instance Segmentation, Linux, Google Cloud Platform (GCP), You Only Look Once (YOLO), Hidden Markov Model, Whisper, CVAT, MLflow, Artificial Intelligence (AI), Action Recognition, AI Modeling, Data Engineering, Machine Learning Operations (MLOps), Cloud, Google Cloud, NVIDIA Triton, NVIDIA Nsight Systems, OpenCV, NVIDIA CUDA, Open Neural Network Exchange (ONNX), Edge AI, ONNX Runtime, Video Processing, Video & Audio Processing, FFmpeg, GPGPU, GPU Computing, Graphics Processing Unit (GPU), Low-latency Software, Semantic Segmentation, Edge Computing
Senior Computer Vision Engineer
2020 - 2024
HAVELSAN
- Designed and developed computer vision-based solutions using Python and C++ for various projects, such as autonomous unmanned ground and aerial vehicles, a maritime patrol aircraft, and video analytic applications for smart cities.
- Researched and created terrain traversability estimation algorithms that use multiple sensor modalities to navigate autonomous ground robots in unstructured outdoor environments.
- Developed 3D surround view systems for automotive applications.
- Investigated deep learning-based computer vision algorithms for autonomous driving.
- Worked on face detection and recognition algorithms.
- Contributed to object detection and tracking algorithms for unpiloted aerial vehicles.
- Explored and developed color correction methods for image and video stitching.
- Designed real-time georeferencing solutions that use GNSS/INS and discrete element method (DEM) data for various platforms.
- Gained experience in algebraic multigrid methods for solving large systems of partial differential equations.
Technologies: C++, Python, PyTorch, OpenCV, Robot Operating System (ROS), GStreamer, PCL, Boost, Eigen, NumPy, SciPy, Git, Data Versioning, PyCharm, Visual Studio Code (VS Code), CMake, Computer Vision, Deep Learning, Convolutional Neural Networks (CNNs), Deep Neural Networks (DNNs), Object Detection, Software Engineering, Embedded Linux, Embedded C++, Machine Learning, Image Processing, Conda, Object-oriented Programming (OOP), Object-oriented Design (OOD), Design Patterns, Linux, Docker, Open Neural Network Exchange (ONNX), LaTeX, NVIDIA Triton, NVIDIA TensorRT, Computer Vision Algorithms, Object Tracking, Artificial Neural Networks (ANN), Artificial Intelligence (AI), Stereoscopic Video, REST APIs, Pandas, Simultaneous Localization & Mapping (SLAM), Facial Recognition, Embedded Systems, Development, DeepStream SDK, NVIDIA Jetson, Image Recognition, C, Self-driving Cars, Hugging Face Transformers, Edge AI, Quantization, model quantization, NVIDIA Jetson Nano, NVIDIA Nsight Systems, Speech-to-Text (STT), Hugging Face, Large Language Models (LLMs), Containerization, CVAT, AI Modeling, Data Engineering, Machine Learning Operations (MLOps), NVIDIA VPI - Vision Programming Interface, Video Processing, NVIDIA CUDA, ONNX Runtime, Video & Audio Processing, FFmpeg, GPGPU, GPU Computing, Graphics Processing Unit (GPU), Low-latency Software, NVIDIA Jetson AGX Orin, Scikit-image, Semantic Segmentation, YOLOv5, MediaPipe, NVIDIA A100 Tensor Core GPU, Edge Computing, Department of Defense
Computer Vision Developer
2022 - 2023
Freelance Client
- Designed and implemented a deep learning-based stereo depth estimation pipeline to work on custom NVIDIA Jetson-based hardware.
- Optimized pipeline for efficiency and accuracy on NVIDIA Jetson. Used TensorRT to optimize/quantize neural networks and CUDA-accelerated functions and kernels to perform fast pre-processing and post-processing.
- Achieved x2 to x4 improvement on both speed and accuracy via optimizations.
Technologies: Computer Vision, Object Detection, Stereoscopic Video, Object Tracking, Stereo Depth Estimation, Python, NVIDIA Jetson, NVIDIA Jetson Nano, NVIDIA CUDA, Deep Learning, PyTorch, ONNX Runtime, Open Neural Network Exchange (ONNX), NVIDIA TensorRT, AI Modeling, Data Engineering, NVIDIA Nsight Systems, NVIDIA VPI - Vision Programming Interface, OpenCV, Embedded Systems, Edge AI, FFmpeg, GPGPU, GPU Computing, Graphics Processing Unit (GPU), Edge Computing
Senior Computer Vision Engineer and Product Owner
2019 - 2020
ArgosAI
- Designed and developed deep learning-based computer vision algorithms for various applications, such as airfield safety and management, industrial inspection, and surveillance.
- Worked extensively on the problem of detecting and classifying FODs (foreign object debris), which are defined as any unwanted objects lying on the runway and apron areas of airports, such as loose hardware and tools, pavement fragments, rocks, etc.
- Contributed as the product owner of A-FOD, an automated remote foreign object debris (FOD) detection system. The system became the flagship product of ArgosAI.
- Designed and developed computer vision and AI algorithms for detecting specific vehicles on apron areas of airfields, such as luggage cars, pushback cars, fuel, and catering trucks, etc., to gather analytics for airside operations.
- Led efforts of PoC projects for two of the largest airports in the world. Worked in close contact with the clients during installation and test phases, addressing their needs and guiding them through a roadmap that best fits their operations.
- Created, trained, and tested deep learning-based neural networks for classification, segmentation, and detection.
- Developed an image processing pipeline with classical computer vision techniques for tasks, such as image registration and foreground and background detection, using various technologies, including C++ STL, Boost, and OpenCV.
- Wrote Python scripts to create, manage, process, and synthesize large image datasets.
- Automated various tasks with Python scripts, such as end-to-end system testing.
Technologies: Computer Vision, Deep Learning, C++, OpenCV, Boost, Keras, TensorFlow, Python, Image Processing, Deep Neural Networks (DNNs), Object Detection, Software Engineering, CMake, Visual Studio Code (VS Code), Databases, Machine Learning, Conda, Object-oriented Programming (OOP), Object-oriented Design (OOD), Computer Vision Algorithms, Artificial Neural Networks (ANN), Artificial Intelligence (AI), Django, Windows Desktop Software, SQLite, Development, Image Recognition, C, Edge AI, Containerization, AI Modeling, Data Engineering, Machine Learning Operations (MLOps), GPGPU, GPU Computing, Graphics Processing Unit (GPU), Scikit-image, Semantic Segmentation, Edge Computing
Senior Software Engineer
2011 - 2018
ASELSAN
- Designed, developed, and maintained real-time embedded software using C and C++ for various military electro-optic systems.
- Developed software for various product families, including handheld thermal cameras, electro-optic sensor systems, and laser warning receiver systems for airborne, naval, and land platforms.
- Led teams of three to five junior software developers and subcontractors. I analyzed requirements, decomposed software projects into basic tasks and activities, and integrated software components.
- Improved the quality and reusability of the software by utilizing object-oriented design principles, design patterns, modular programming, and unit testing.
- Contributed to non-uniformity correction, bad pixel replacement, and image enhancement algorithms for thermal images.
- Designed and developed reusable software modules for various components and hardware architectures.
- Managed software through the entire lifecycle in CMMI level 3-compliant processes using requirements management, source control, and issue tracking tools.
Technologies: C++, Embedded C, Embedded C++, Embedded Linux, Real-time Operating System (RTOS), Image Processing, Microcontrollers, Algorithms, Software Engineering, CMake, Computer Vision, MATLAB, Electronics, Subversion (SVN), Object-oriented Programming (OOP), Object-oriented Design (OOD), Design Patterns, Linux, C#, DOORS, .NET, Optics, LaTeX, Windows Desktop Software, C#.NET, SQLite, Embedded Systems, Development, C, Real-time Embedded Systems, Low-latency Software, Real-time Systems, Edge Computing, Thermal Imaging, Department of Defense
R&D Engineer (Part-time)
2010 - 2011
SDT Space & Defence Technologies
- Implemented an FPGA-based SD card controller for recording and playing streaming videos that can be managed from a graphical user interface.
- Programmed FPGA using VHDL and Xilinx Ise while coding in behavioral and register-transfer level (RTL).
- Gained hands-on experience with serial peripheral interface (SPI), Secure Digital, and JPEG 2000 standards.
- Developed graphical user interfaces using Borland C++.
- Built applications with TI MSP430 microcontrollers utilizing communication and analog-to-digital converter modules.
Technologies: FPGA, VHDL, Microcontrollers, Software Engineering, Electronics, Image Processing, C++, Windows Desktop Software, Embedded Systems, Development, C, Low-latency Software, Real-time Systems, Edge Computing, Department of Defense
Project History
HyperE2VID: Improving Event-based Video Reconstruction via Hypernetworks
A research manuscript that has been submitted to the scientific journal "IEEE Transactions on Image Processing."
Abstract: Event-based cameras are becoming increasingly popular for their ability to capture high-speed motion with low latency and high dynamic range. However, generating videos from events remains challenging due to the highly sparse and varying nature of event data. To address this, in this study, we propose HyperE2VID, a dynamic neural network architecture for event-based video reconstruction. Our approach uses hypernetworks and dynamic convolutions to generate per-pixel adaptive filters guided by a context fusion module that combines information from event voxel grids and previously reconstructed intensity images. We also employ a curriculum learning strategy to train the network more robustly. Experimental results demonstrate that HyperE2VID achieves better reconstruction quality with fewer parameters and faster inference time than the state-of-the-art methods.
Abstract: Event-based cameras are becoming increasingly popular for their ability to capture high-speed motion with low latency and high dynamic range. However, generating videos from events remains challenging due to the highly sparse and varying nature of event data. To address this, in this study, we propose HyperE2VID, a dynamic neural network architecture for event-based video reconstruction. Our approach uses hypernetworks and dynamic convolutions to generate per-pixel adaptive filters guided by a context fusion module that combines information from event voxel grids and previously reconstructed intensity images. We also employ a curriculum learning strategy to train the network more robustly. Experimental results demonstrate that HyperE2VID achieves better reconstruction quality with fewer parameters and faster inference time than the state-of-the-art methods.
EVREAL: Towards a Comprehensive Benchmark and Analysis Suite for Event-based Video Reconstruction
A research paper that has been accepted to the 4th International Workshop on Event-based Vision at CVPR 2023.
Abstract: Event cameras are a new type of vision sensor that incorporates asynchronous and independent pixels, offering advantages over traditional frame-based cameras, such as high dynamic range and minimal motion blur. However, their output is not easily understandable by humans, making the reconstruction of intensity images from event streams a fundamental task in event-based vision. While recent deep learning-based methods have shown promise in video reconstruction from events, this problem is not completely solved yet. To facilitate comparison between different approaches, standardized evaluation protocols and diverse test datasets are essential. This paper proposes a unified evaluation methodology and introduces an open-source framework called EVREAL to comprehensively benchmark and analyze various event-based video reconstruction methods from the literature. Using EVREAL, we give a detailed analysis of the state-of-the-art methods for event-based video reconstruction and provide valuable insights into the performance of these methods under varying settings, challenging scenarios, and downstream tasks.
Abstract: Event cameras are a new type of vision sensor that incorporates asynchronous and independent pixels, offering advantages over traditional frame-based cameras, such as high dynamic range and minimal motion blur. However, their output is not easily understandable by humans, making the reconstruction of intensity images from event streams a fundamental task in event-based vision. While recent deep learning-based methods have shown promise in video reconstruction from events, this problem is not completely solved yet. To facilitate comparison between different approaches, standardized evaluation protocols and diverse test datasets are essential. This paper proposes a unified evaluation methodology and introduces an open-source framework called EVREAL to comprehensively benchmark and analyze various event-based video reconstruction methods from the literature. Using EVREAL, we give a detailed analysis of the state-of-the-art methods for event-based video reconstruction and provide valuable insights into the performance of these methods under varying settings, challenging scenarios, and downstream tasks.
ArgosAI A-FOD
https://argosai.com/foreign-object-detection/An AI and computer vision-based automated remote FOD detection system.
I designed, trained, and tested deep learning-based neural networks for computer vision tasks, such as classification, segmentation, and detection, using Python, Keras, and TensorFlow. I also developed an image processing pipeline with classical computer vision techniques for image registration and foreground/background detection utilizing C++ STL, Boost, and OpenCV. Finally, I wrote Python scripts to create, manage, process, and synthesize large image datasets and automate various tasks, including end-to-end system testing.
I designed, trained, and tested deep learning-based neural networks for computer vision tasks, such as classification, segmentation, and detection, using Python, Keras, and TensorFlow. I also developed an image processing pipeline with classical computer vision techniques for image registration and foreground/background detection utilizing C++ STL, Boost, and OpenCV. Finally, I wrote Python scripts to create, manage, process, and synthesize large image datasets and automate various tasks, including end-to-end system testing.
HAVELSAN BARKAN Autonomous Medium-class UGV System
An autonomous unmanned ground vehicle.
I researched, designed, developed, and optimized terrain traversability estimation algorithms for this system. I also implemented software written in C++ and based it on the Robot Operating System (ROS), which fuses information from multiple sensory modalities, such as cameras and LiDARs. The software works on NVIDIA Jetson AGX Xavier devices in real time, enabling the navigation of an autonomous ground robot in unstructured outdoor environments. Finally, I implemented a ROS-based software package to visualize a terrain traversability map on the video coming from an onboard camera.
I researched, designed, developed, and optimized terrain traversability estimation algorithms for this system. I also implemented software written in C++ and based it on the Robot Operating System (ROS), which fuses information from multiple sensory modalities, such as cameras and LiDARs. The software works on NVIDIA Jetson AGX Xavier devices in real time, enabling the navigation of an autonomous ground robot in unstructured outdoor environments. Finally, I implemented a ROS-based software package to visualize a terrain traversability map on the video coming from an onboard camera.
HAVELSAN ADVENT MARTI Air Command and Control System
A high-technology air command and control system.
I worked on object (ships) detection algorithms and real-time georeferencing software that uses GNSS/INS and DEM data to calculate the coordinates of detected objects accurately.
I worked on object (ships) detection algorithms and real-time georeferencing software that uses GNSS/INS and DEM data to calculate the coordinates of detected objects accurately.
HAVELSAN BAHA Autonomous Aircraft
A fixed-wing sub-cloud autonomous aircraft that can take off and land vertically.
I developed real-time georeferencing software that uses GNSS/INS and DEM data to accurately calculate the coordinates of targets that are tracked with a camera.
I developed real-time georeferencing software that uses GNSS/INS and DEM data to accurately calculate the coordinates of targets that are tracked with a camera.
ASELSAN Laser Warning Receiver System
An advanced military electro-optic system to detect, classify, identify, and warn of hostile laser threats aiming at a platform—airborne, naval, or land—in a short time with high sensitivity.
I was the leading software developer of the system for five years while the system was rigorously evaluated with qualification tests. During this time, I developed real-time embedded software in C to process sensory data and handle all the communication and control system requirements. I optimized laser threat detection and recognition algorithms and contributed to many software packages that support the main project, such as simulation and test applications.
I was the leading software developer of the system for five years while the system was rigorously evaluated with qualification tests. During this time, I developed real-time embedded software in C to process sensory data and handle all the communication and control system requirements. I optimized laser threat detection and recognition algorithms and contributed to many software packages that support the main project, such as simulation and test applications.
Synthetic18k | Published Paper on the Use of Synthetic Person Images for Representation Learning
An article published in Signal Processing: Image Communication Scientific Journal.
Here we first introduce a large-scale synthetic dataset called Synthetic18K. Then, we demonstrate that the pretraining of simple deep architectures on Synthetic18K for person re-identification, attribute recognition, and fine-tuning on real data leads to significant improvements in prediction performances. I mainly worked on training and validation of deep neural networks on person re-identification and attribute recognition tasks, also contributing to writing the original draft of the article.
Here we first introduce a large-scale synthetic dataset called Synthetic18K. Then, we demonstrate that the pretraining of simple deep architectures on Synthetic18K for person re-identification, attribute recognition, and fine-tuning on real data leads to significant improvements in prediction performances. I mainly worked on training and validation of deep neural networks on person re-identification and attribute recognition tasks, also contributing to writing the original draft of the article.
A Real-time 3D Surround View Pipeline for Embedded Devices
https://www.scitepress.org/Papers/2022/107665/pdf/index.htmlA paper published at the 17th International Conference on Computer Vision, Theory and Applications | VISAPP 2022.
Here we propose an end-to-end algorithm pipeline for 3D surround view systems that work on embedded devices in real time. I mainly worked on the color correction part of the pipeline, designing and implementing a local color correction method based on Poisson image editing. I used an algebraic multi-grid solver from AmgX (a GPU accelerated library) to solve the resulting large and sparse system of linear equations. Then, I optimized this algorithm to work on resource-constrained embedded devices in real time. Finally, I contributed to the experimental set up and the paper writing.
Here we propose an end-to-end algorithm pipeline for 3D surround view systems that work on embedded devices in real time. I mainly worked on the color correction part of the pipeline, designing and implementing a local color correction method based on Poisson image editing. I used an algebraic multi-grid solver from AmgX (a GPU accelerated library) to solve the resulting large and sparse system of linear equations. Then, I optimized this algorithm to work on resource-constrained embedded devices in real time. Finally, I contributed to the experimental set up and the paper writing.
ASELSAN Mini-TWS Thermal Weapon Sight
A light thermal weapon sight with excellent image quality and high range performance.
I was the system's leading software developer for four years. During this time, the project has evolved from prototypes to thousands of devices produced and sold. I designed and developed embedded software in C++ to cover a wide range of product features, including thermal image acquisition and enhancement, communication and control, built-in tests, on-screen displays, and button controls.
I was the system's leading software developer for four years. During this time, the project has evolved from prototypes to thousands of devices produced and sold. I designed and developed embedded software in C++ to cover a wide range of product features, including thermal image acquisition and enhancement, communication and control, built-in tests, on-screen displays, and button controls.
ASELSAN FALCONEYE | Electro-optical Sensor System
An integrated military electro-optic sensor system that incorporates a thermal and daylight camera, laser range finder, digital magnetic compass, and GPS-based locator.
I was the system's leading software developer for four years, creating embedded software while the system was continuously updated with new features and changing components. I designed the system's software with many features, including thermal image acquisition, enhancement, and target coordinate calculation.
I was the system's leading software developer for four years, creating embedded software while the system was continuously updated with new features and changing components. I designed the system's software with many features, including thermal image acquisition, enhancement, and target coordinate calculation.
ASELSAN YAMGOZ Enhanced 360 Degree Close Range Surveillance System
A compact, high-performance vision system designed for tanks and other armored vehicles.
The system provides enhanced maneuvering capability and situational awareness under severe conditions. It uses thermal and daylight sensors, covering a 360° field of view. I was the leading developer of the system's embedded software for two years. During this time, the system was designed and prototyped from scratch.
The system provides enhanced maneuvering capability and situational awareness under severe conditions. It uses thermal and daylight sensors, covering a 360° field of view. I was the leading developer of the system's embedded software for two years. During this time, the system was designed and prototyped from scratch.
ORGenie: The AI-driven Solution for Operating Room Excellence
https://exinhealth.ai/ORGenie is a smart artificial intelligence platform that continuously and objectively supports operating rooms, helping to improve the efficiency of surgical operations and reduce patient safety risk factors.
HAVELSAN EYEMINER
A video analysis system supported by artificial intelligence that efficiently analyzes data from imaging systems via computer vision algorithms. It features analytics such as video summarization, person identification, passenger and driver violation detection, suspicious object and person detection, plate recognition, parking violation detection, and more.
Education
2017 - 2024
PhD in Computer Science
Hacettepe University - Ankara, Turkey
2012 - 2015
Master's Degree in Engineering Management
Middle East Technical University - Ankara, Turkey
2006 - 2011
Bachelor's Degree in Electrical and Electronics Engineering
Middle East Technical University - Ankara, Turkey
Certifications
JULY 2022 - PRESENT
Deep Learning Engineer
Workera
OCTOBER 2021 - PRESENT
Master CMake for Cross-Platform C++ Project Building
Udemy
SEPTEMBER 2021 - PRESENT
CUDA Programming Masterclass with C++
Udemy
AUGUST 2021 - PRESENT
Complete Modern C++ (C++11/14/17)
Udemy
JULY 2020 - PRESENT
Certificate of Participation in the EEML2020 Summer School
EEML – Eastern European Machine Learning Summer School
JUNE 2018 - PRESENT
GPU Programming
Middle East Technical University (METU) Informatics Institute
FEBRUARY 2018 - PRESENT
Linux System Calls
UCanLinux
JULY 2017 - PRESENT
Embedded Linux
UCanLinux
APRIL 2017 - PRESENT
Embedded C and C++ Unit Testing
First Technology Transfer (FTT)
MARCH 2017 - PRESENT
Altera SoC Training
Doulos
SEPTEMBER 2016 - PRESENT
Programming in C#
Infopark
JULY 2015 - PRESENT
Using DOORS for Requirements Management
PROYA
APRIL 2014 - PRESENT
C6000 Embedded Design Workshop Using SYS/BIOS
Texas Instruments
FEBRUARY 2012 - PRESENT
Optical Design
ASELSAN
Skills
Libraries/APIs
PyTorch, NumPy, OpenCV, Hugging Face Transformers, TensorFlow, Keras, Pandas, FFmpeg, Scikit-learn, PCL, Eigen, SciPy, ZeroMQ, Matplotlib, REST APIs
Tools
PyCharm, Git, You Only Look Once (YOLO), Open Neural Network Exchange (ONNX), NVIDIA Jetson, CVAT, MATLAB, Slack, Subversion (SVN), LaTeX, DOORS, NVIDIA Nsight Systems, Hidden Markov Model, Whisper, Scikit-image, CMake
Languages
C++, Embedded C, Python, C, C++11, Embedded C++, C++14, C#, VHDL, C++17, SQL, C#.NET
Paradigms
GPGPU, Real-time Systems, Siamese Neural Networks, Object-oriented Programming (OOP), Object-oriented Design (OOD), Design Patterns, Unit Testing, Parallel Programming
Platforms
Visual Studio Code (VS Code), NVIDIA CUDA, NVIDIA Jetson AGX Orin, Ubuntu, Linux, Embedded Linux, BeagleBone Black, Docker, Google Cloud Platform (GCP)
Frameworks
GStreamer, Boost, Qt, Google Test, .NET, Django, Django REST Framework, MediaPipe
Storage
Databases, SQLite, Google Cloud
Other
Image Processing, Machine Learning, Computer Vision, Deep Learning, Research, Object Detection, Neural Networks, Deep Neural Networks (DNNs), Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), Microcontrollers, Software Engineering, Event-based Vision, Artificial Intelligence (AI), Software Development, NVIDIA Triton, NVIDIA TensorRT, Computer Vision Algorithms, Artificial Neural Networks (ANN), Facial Recognition, Embedded Systems, Development, Image Recognition, Edge AI, Quantization, model quantization, NVIDIA Jetson Nano, Speech-to-Text (STT), Hugging Face, MLflow, ONNX Runtime, AI Modeling, Data Engineering, Machine Learning Operations (MLOps), NVIDIA VPI - Vision Programming Interface, Video Processing, Real-time Embedded Systems, Video & Audio Processing, GPU Computing, Graphics Processing Unit (GPU), Low-latency Software, Semantic Segmentation, YOLOv5, Residual Neural Networks (ResNets), Edge Computing, Thermal Imaging, Department of Defense, Operating Systems, Data Structures, Microprocessors, Real-time Operating System (RTOS), Robot Operating System (ROS), Mathematics, Conda, Embedded Software, Writing & Editing, Windows Desktop Software, Self-driving Cars, Containerization, Digital Signal Processing, Electronics, Data Mining, Statistics, Monte Carlo Simulations, Economics, Strategic Planning, Decision Modeling, Operations Management, Optimization, Text Mining, Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Discrete Mathematics, Algorithms, Programming Languages, FPGA, Data Versioning, Data Science, Autonomous Robots, Robotics, Differential Equations, Partial Differential Equations, Autonomous Navigation, Linux System Calls, System-on-a-Chip (SoC), Optics, Grant Proposals, Object Tracking, Stereoscopic Video, Simultaneous Localization & Mapping (SLAM), Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), DeepStream SDK, Voxel, Large Language Models (LLMs), Audio Processing, Speech Recognition, Automatic Speech Recognition (ASR), Instance Segmentation, Action Recognition, Stereo Depth Estimation, Cloud, SIMD, User Interface (UI), NVIDIA A100 Tensor Core GPU
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