Exploring the new Anschuetz GmbH + FarSounder integration 🙌 What's included: 🔹Argos 3D FLS data overlay on ECDIS Chart 🔹SonaSoft LT™ interface accessible within SYNAPSIS NX 🔹Visualization of both in-water targets and live/historical seafloor data 🔹Filtering tools to adjust data by depth and signal level 🔹Multiple color schemes for data visualization Visit FarSounder's stand 08.605 in Hall 8 at Metstrade to learn more and catch a live demo of this powerful collaboration in action. #yachting #oceanexploration #synapsis #newbuild #refit #maritimenavigation #3Dsonar

FarSounder's new integration of our #3DForwardLookingSonar with the Anschuetz GmbH's SYNAPSIS (W)ECDIS NX is packed with great features! This integration supports direct overlay of FarSounder's #3DFLS data as a layer on the SYNAPSIS charts as well as display of our SonaSoft LT app inside a separate window. Great work Heath Henley (FarSounder) and Ingo S. (Anschutz) for making this happen! This new functionality will be a great value for all types of vessels including #Superyachts, #NavalVessels, #PatrolCraft, and #CoastGuards.

UBTECH Walker Tienkung remote operation and data acquisition workstation in IROS. Based on real-world scenarios, the Walker Tienkung robot performs tasks (transportation, sorting, grasping) through its isomorphic-arm remote control system, with end-side software managing complete task data in real time.

Behind every cryo-EM breakthrough is an intelligent team, microscope—and the software—that made it possible. Our Thermo Scientific Smart EPU Software drives single particle analysis data collection with AI-powered automation and real-time processing for an accelerated path from sample to structure. Watch how it works: https://bit.ly/4oEWoCg #SmartEPU #CryoEM #SingleParticleAnalysis #AutomatedCryoEM

🔲 RF-DETR SEG (PREVIEW): ROBOFLOW'S REAL-TIME TRANSFORMER SETS A NEW STANDARD IN INSTANCE SEGMENTATION. 👉 RF-DETR Seg (Preview) extends Roboflow’s RF‑DETR family with an instance‑segmentation head that claims up to 3× faster inference and higher accuracy than the largest YOLO11 model on the MS COCO segmentation benchmark. 👉 The code and models are released under an Apache‑2.0 license, enabling easy adoption and fine‑tuning across real‑world applications. 🟥 follow globalnetwork video: Dragos Stan / globalnetwork Roboflow YOLOvX Ultralytics #Roboflow #YOLOvX #Ultralytics

Most teams don’t need more tools they need faster ways to turn data into insight. That’s where automation makes the difference. What used to take days of photogrammetry setup and manual processing can now happen automatically creating accurate 2D and 3D inspection models ready for analysis in hours, not weeks. No more waiting for specialists or external processing. Just upload, generate, and start inspecting. Because in infrastructure, speed and accuracy aren’t trade-offs they’re requirements. Curious about the gNext difference? Book a demo at the link in the first comment.

Key Architectural Innovation: Centralized Control Bus The equivalent major innovation here is decentralized mechanical motion with centralized intelligence. The hands act like “peripherals” … simple, low-cost endpoints tethered to a high-bandwidth controller (hence TetherIA). This separation of mechanical function from cognitive load allows scalability + many cheap manipulators controlled by a single intelligent system. Lesson: modular distributed mechanics + centralized intelligence = scalable, maintainable robot networks.

🚀 𝗕𝗼𝗼𝘀𝘁 𝗬𝗼𝘂𝗿 𝗠𝗕𝗗 𝗦𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻𝘀: 𝗠𝗮𝘀𝘁𝗲𝗿𝗶𝗻𝗴 𝗕𝗮𝘁𝗰𝗵 𝗥𝘂𝗻𝘀 𝘄𝗶𝘁𝗵 𝗔𝗱𝗮𝗺𝘀 𝗜𝗻𝘀𝗶𝗴𝗵𝘁   Learn how to automate repetitive simulation tasks and explore design variations efficiently with Adams Insight. Our latest guide walks you through setting up batch runs to save time, improve consistency, and extract deeper insights from your models.   👉 𝗥𝗲𝗮𝗱 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗴𝘂𝗶𝗱𝗲 𝗵𝗲𝗿𝗲: https://lnkd.in/dUYiAf69   #Adams #Simulation #MBD #Engineering #DesignOptimization #Automation

The secret sauce of Quanscient Allsolve — visually explained In this clip from our recent demo video, we highlight one of Allsolve's most important capabilities: → The ability to not only split a large problem into smaller pieces for faster solving, but also run hundreds of these simulations in parallel. This capability can massively increase overall engineering throughput while reducing runtimes by more than 99%. See the cool visualization of this in the clip below, and watch the full demo on our website!

After experimenting with SAM2 for plant segmentation, I decided to take things one step further and train my own model. Using Roboflow and YOLOv11-seg, I annotated about 100 images of plants, added some augmentations, and trained a custom instance segmentation model directly in Google Colab - following this great tutorial: https://lnkd.in/d-jBBcrv. Within minutes I had a fully fine-tuned YOLOv11 model on my own data - and the results are fantastic. Next, I'll run inference on a few hundred new RGB images, use the resulting masks to isolate the same regions in my aligned thermal images, and start extracting agricultural insights by combining the visual and thermal data. It's amazing how accessible this workflow has become - from annotation to a production-ready segmentation model, all in a single Colab notebook. #ComputerVision #AgTech