Dell Technologies
Dell Validated Design Solution for Computer Vision Restoration
ProHawk Vision was tested and validated by Dell Technologies as a Dell Validated Design Solution for Computer Vision. The Dell Validation Labs rigorously tested the ProHawk Vision Server, leading to the publication of a comprehensive white paper that showcases the solution’s exceptional capabilities in video and image restoration for computer vision AI applications.
The Dell Validation Labs evaluation including hardware compatibility, integration capabilities, and real-world scenarios concluding with a new Dell/ProHawk capability including:
- Transformed Video Clarity: ProHawk’s video restoration technology significantly improves the quality and clarity of video feeds, ensuring that vital details are captured fully and earlier.
- Accelerated Analytics: ProHawk AI streamlines video analytics, reducing the time required to process (less than 3 milliseconds) and analyze video data, critical for real-time decision-making.
- Improved Accuracy: ProHawk’s advanced algorithms enhance computer vision accuracy, identifying more objects, faster, reducing false positives and increasing the reliability of results.
- Scalability: ProHawk seamlessly integrates with Dell hardware, ensuring scalability to meet the demands of both small and large-scale deployments across multiple industries
- 24/7 Operations: Video in daytime or perfect environmental conditions is actionable, but environmental conditions are never perfect.
By solving for poor visibility conditions such as low light, haze, and obscured objects, ProHawk facilitates quick decision-making and response time without the need for additional equipment or staff. For example, in the side by side images below, this helps organizations meet safety and security requirements, in high-risk areas and challenging environments.
ProHawk AI Video Restoration Education Series
Computer Vision Restoration 100 – Computer Vision Real World Environments
The main problem that ProHawk AI resolves for customers are poor visibility real-world environment conditions. There are hundreds of video analytics companies focused on training AI to interpreting video to drive vehicles, deliver security, empower robotics, and better understand the real-world around us. The problem is poor visibility creates poor imagery. Various factors in an environment can contribute to poor visibility, including light issues, weather, sensor quality, obstacles in the environment, and particulate matter, which are various sized particles suspended in the environment. This session will provide a quick 8 minute overview of what to expect when deploying cameras and AI in the real world.
Computer Vision Restoration 101 – Video & Imagery Challenges & Problems
Computer Vision, Artificial Intelligence, and deep learning promise to revolutionize automation in scores of industries and applications. A major problem of AI systems trained on pristine imagery are errors due to the inability to interpret real-world, unconstrained environments where video is less than perfect. According to the IEEE, “To half the error rate, you can expect to need more than 500 times the computational resources.”
ProHawk contends that this promise to revolutionize automation cannot be achieved if the quality of the video and images are poor.
Computer Vision Restoration 201 – Industries & Market Applications
Through ProHawk’s partnerships with NVIDIA and Dell Technologies, we have identified eight major industries that can take advantage of the benefits ProHawk Vision can provide to them. These industries include: Critical Infrastructure, Energy, Transportation, Healthcare, Manufacturing, Finance, Agriculture, and Retail. Each of these industries has several AI applications that can significantly benefit from ProHawk Vision’s computer vision restoration capabilities.
Computer Vision Restoration 301 – Computer Vision Deployment Models
This session provides the deployment models and various ways to quickly and easily integrate ProHawk Vision products with live camera streams to dramatically enriches the quality of Video Management System streams and recorded video with latency as low as 3 milliseconds that is undetectable to the human eye. The ProHawk Vision product line is based on patented automated environmental restoration algorithms that corrects noisy, obscured, or unclear video into sharp, clear, visible video with intricate details, powered by Dell Workstations & Servers leveraging NVIDIA frameworks and parallel processing GPUs. ProHawk products are driven by five patented industry-leading Computer Vision automated restoration algorithms that reveal each pixel’s true representation based on light reflection and refraction of particulates, automatically producing live video that is intelligible for humans and computers. These improvements enable superior AI with earlier and more detections at higher confidence levels without the need to retrain existing AI models.
Computer Vision Restoration 401 – ProHawk Vision Restoration Algorithms
Learn about the patented ProHawk Vision restoration algorithms to resolve unclear video due to difficult challenging conditions such as: weather, lighting, darkness, particulates, and other environments. Learn how each algorithms works, and how it can be utilized in a variety of problems real-world environments and conditions. Algorithms will cover a variety of areas critical to resolving optical difficulties, including: tone; contrast; color; motion; dynamic range; edge sharpening, visual noise reduction; logical & system restoration; automatic contrast; and automatic restoration.
ProHawk AI for Computer Vision Restoration
- Increases the effective range of your cameras in video surveillance systems.
- Dramatically improves the performance of your video analytics systems reducing costs of false positive alarms.
- Helps improve the performance of facial and license plate recognition.
- Reduce costs and requirements for infrared and other perimeter illuminators.
- Cuts glare and improves detail in overexposed conditions.
- Removes shadows and reveals detail in low-light scenes.
- Increase reliability of thermal cameras ability to differentiate body heat from ambient surrounds.
- Reduces interference caused by rain, snow, smoke, fog, dust and other forms of particulate matter for accurate identification.