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Using AI and deep learning, we provide AI platforms and ML services for image recognition and analytics solutions, delivering enterprise-level image processing and analysis software.
01
AI Image Analytics Service
Collect and label large image datasets, train machine learning models, and continuously optimize algorithms to generate highly accurate Image Recognition Models.
Build industry-specific image recognition and analysis platforms using client-provided Expertise or Algorithm Packages.
02
AI Image Analytics Service
03
AI Image Analytics Service
Integrate traditional smart hardware with AI recognition algorithms to create Advanced AI-powered Hardware Products featuring image recognition and analysis capabilities.
Help doctors diagnose diseases
Improve computer understanding
Improve image quality or create new visual effects
Automatically detect & alert non-standard activity
Automatically detect product defects
Zed has a specialized AI image processing algorithm development team to address clients' hardware and software needs.
Using TensorFlow、TensorFlow Lite、PyTorch for tools and libraries to build, train deep neural networks.
Using OpenCV and OpenMV for image processing, feature detection, and image recognition.
Using algorithms including Classification, Regression, and Clustering for image analysis and processing.
Applying techniques such as Filtering, Sharpening, and Contrast Enhancement to improve image quality.
Utilizes deep learning and other AI technologies to meet specialized image recognition and analysis needs.
Uses lightweight model fusion and compression to boost algorithm efficiency, achieving millisecond-level analysis.
Provides standardized interfaces for easy integration, with robust security measures for protection.
Tailors computational resources to specific application requirements, aligning algorithms with real-world use cases.
Assisted a research institute in developing a tunnel scanning electron microscope (SEM) control system. The system provides real-time feedback on the SEM's status, controls sample scanning according to the scanning plan, and analyzes energy spectrum data.
Developed a system consisting of two main components: injection and imaging. The software integrates with industrial cameras to receive video streams, captures screenshots, and identifies droplets within the images. It then predicts deformation and analyzes stress based on the droplet contours.
Developed a training management system for a medical university to oversee in-house courses. The system features modules for course design, project planning, and scheduling. It captures real-time footage of student practice with hardware and uses neural networks
Developed an upper-level control system for biological microscopes, integrating with a three-axis microscope control unit and industrial camera for high-resolution imaging of human tissues. The system applies traditional and neural network algorithms for image processing tasks, including convolution superpixels, depth of field, automatic segmentation, staining, and target recognition.
Assisted a research institute in developing a tunnel scanning electron microscope (SEM) control system. The system provides real-time feedback on the SEM's status, controls sample scanning according to the scanning plan, and analyzes energy spectrum data.
Developed a system consisting of two main components: injection and imaging. The software integrates with industrial cameras to receive video streams, captures screenshots, and identifies droplets within the images. It then predicts deformation and analyzes stress based on the droplet contours.
Developed a training management system for a medical university to oversee in-house courses. The system features modules for course design, project planning, and scheduling. It captures real-time footage of student practice with hardware and uses neural networks
Developed an upper-level control system for biological microscopes, integrating with a three-axis microscope control unit and industrial camera for high-resolution imaging of human tissues. The system applies traditional and neural network algorithms for image processing tasks, including convolution superpixels, depth of field, automatic segmentation, staining, and target recognition.
Assisted a research institute in developing a tunnel scanning electron microscope (SEM) control system. The system provides real-time feedback on the SEM's status, controls sample scanning according to the scanning plan, and analyzes energy spectrum data.
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IoT Architect & Data Analyst
IoT Industry Solution Strategist
AI & IoT Application Analyst
Hardware Specialist
Product Designer
Need a Custom IoT Solution?
Book an online meeting with our IoT specialists to discuss your project needs.
Try our services free for one week to see the value we offer.
Mobile APP & Embedded Expert
IoT Architect & Data Analyst
IoT Industry Solution Strategist
AI & IoT Application Analyst
Hardware Specialist
Product Designer
Need a Custom IoT Solution?
Book an online meeting with our IoT specialists to discuss your project needs.
Try our services free for one week to see the value we offer.