Ben Chan ♦ Insightful. Innovator. Achiever.’s Post

Finding ghosts through thermal imaging may be a thing of the past. AI was used to sharpen blurry thermal images, leaving benign but accurate results. #AI #ML #futurism #IntelligenceFactory #digitaltransformation #DX https://lnkd.in/gYj69VMc

Finding ghosts through thermal imaging may be a thing of the past. AI was used to sharpen blurry thermal images, leaving benign but accurate results. #AI #ML #futurism #IntelligenceFactory #digitaltransformation #DX https://lnkd.in/gVGSkBfD

Finding ghosts through thermal imaging may be a thing of the past. AI was used to sharpen blurry thermal images, leaving benign but accurate results. #AI #ML #futurism #IntelligenceFactory #digitaltransformation #DX https://lnkd.in/eNMx4zRY

Participate in the AI for Image Processing Applications on Traffic: Advancements, Challenges, and Opportunities (AI4IPoT) Workshop! This workshop is designed as a leading forum to explore complex challenges and opportunities in intelligent traffic systems. Learn more: https://hubs.la/Q02vB9Mr0

We at Elomatic are developing automated tools and processes that revolutionize the use of data for object detection 💻🔎 Object detection is a crucial technology in various fields, including digital twins, robotics, and artificial intelligence. It can be utilized for indenting and localizing objects in images, videos, lidar, and point cloud data, for example. Object detection plays a key role in various sectors, for example: ✅Autonomous vehicles rely on it for safe navigation. ✅Surveillance systems use it for security and anomaly detection. ✅In medical field, it aids in precise imaging and diagnosis. ✅Retailers leverage it for accurate inventory management and customer analytics. ✅Manufacturing quality control also benefits from it by identifying defects and improving production efficiency. Our Specialist in Digital Business Development, Petri Seppänen, writes in our newest blog post that there are a few things you should be aware of if you plan to use object detection. For example, its use requires a lot of training, in which human labor is usually unavoidable. That is why we are developing the automated tools. Read what other things you should consider when implementing the technology: https://lnkd.in/dbrMicsR #objectdetection #AI #artificialintelligence #digitaltwin #robotics #Elomatic #BuildingTomorrow

#Technology within the #Transport space is evolving rapidly. With new technology comes new words to describe it. Some of these have obvious definitions, whereas others are a little less straightforward. Orcoda has compiled the most common terms used in the transport tech space. Read Here: https://bit.ly/3L4xJVQ #AI #AR #ElectricVehicle #Telematics #Biometrics #Electrification #GenAI #Geofencing #ML #LLM #V2X

🖼️ Advancing Image Reconstruction and Segmentation! 🌐✂️ Image reconstruction and segmentation are pushing the boundaries of AI, enhancing medical imaging 🏥, autonomous driving 🚗, and more. Exciting breakthroughs in deep learning 🧠🔍 are paving the way for sharper images 📸 and precise object detection 🎯. Thrilled to witness these transformative advancements! 🚀💡 #ImageReconstruction #ImageSegmentation #DeepLearning #AI #Innovation

Our ideas about the #Terminator T800 are outdated. In reality, it will not just have thermal vision, but will actually be able to see almost everything )). #ai #artificialintelligence #computervision #robots

Researchers from the University of Zurich have developed a bio-inspired camera hybrid system that can detect obstacles around a car faster than current systems. Most current cameras are frame-based, capturing snapshots at regular intervals. Those used for driver assistance in cars typically capture 30 to 50 frames per second. An artificial neural network can be trained to recognise objects in these images, such as pedestrians, bikes, and other cars. However, if something happens in the 20 to 30 milliseconds between two snapshots, the camera may detect it too late. The new hybrid system features a standard camera that captures 20 images per second. These images are processed by a convolutional neural network, an AI system trained to recognise cars and pedestrians. Using both a standard camera and an event camera, their system anticipates movements in real time, ensuring no blind spots. Read more https://bit.ly/3yZlYND #RoadSafety #AI #AutonomousDriving #TechForGood #RandD #RandDProjects #RandDtaxRelief #TaxConsultant #Consultancy

AI advancements are not just about seeing and understanding but about enabling machines to act and learn in 3D space. Spatial intelligence in AI will allow for more profound interactions with the real world, enhancing productivity and human experience. One of the most effective use case is using AI-powered smart sensors to monitor clinician practices, track surgical instruments, prevent patient falls, and pilot autonomous robots to transport medical supplies. Other one can be by using the robots to do everyday tasks by patients using EEG cap.