AI Image Analysis and Processing Platform Development
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.
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Algorithm Model Generation Using Machine Learning
Collect and label large image datasets, train machine learning models, and continuously optimize algorithms to generate highly accurate Image Recognition Models.
Develop Custom Image Analysis Software for Business Needs
Build industry-specific image recognition and analysis platforms using client-provided Expertise or Algorithm Packages.
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Custom Development of AI Smart Hardware Products
Integrate traditional smart hardware with AI recognition algorithms to create Advanced AI-powered Hardware Products featuring image recognition and analysis capabilities.
Image Analysis and Processing Application Scenarios
Medical Diagnosis
Help doctors diagnose diseases
Pathology Analysis
Blood Analysis
Disease Diagnosis
Imaging Diagnosis
Image Recognition
Improve computer understanding
Facial Recognition
Vehicle Recognition
Fire Detection
Smoke Detection
Image Processing
Improve image quality or create new visual effects
Image Denoising
Image Dehazing
Image Segmentation
Image Optimization
User Behavior Analysis
Automatically detect & alert non-standard activity
Posture Analysis
Smoking Behavior
Phone Call
Dress Code
Industrial Inspection
Automatically detect product defects
Missing Part Detection
Dimension Inspection
Burr Detection
Appearance Inspection
Zed Technical Expertise
Zed has a specialized AI image processing algorithm development team to address clients' hardware and software needs.
Deep Learning Frameworks
Using TensorFlow、TensorFlow Lite、PyTorch for tools and libraries to build, train deep neural networks.
Computer Vision Libraries
Using OpenCV and OpenMV for image processing, feature detection, and image recognition.
Machine Learning Algorithms
Using algorithms including Classification, Regression, and Clustering for image analysis and processing.
Image Enhancement Tech
Applying techniques such as Filtering, Sharpening, and Contrast Enhancement to improve image quality.
ZedIoT Service Advantages
Advanced Technology
Utilizes deep learning and other AI technologies to meet specialized image recognition and analysis needs.
Fast Response
Uses lightweight model fusion and compression to boost algorithm efficiency, achieving millisecond-level analysis.
Secure and Reliable
Provides standardized interfaces for easy integration, with robust security measures for protection.
Flexible Solutions
Tailors computational resources to specific application requirements, aligning algorithms with real-world use cases.
Case Study
Industrial Camera Image Recognition
Droplet Deformation Stress Analysis System Development
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.
Medical University Behavior Recognition and Image Analysis
Practical Training Management Behavior Recognition System Development
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
Medical Device Company
Biological Microscope Control System Development
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.
Tunnel Scanning
Electron Microscope Control and Data Analysis System Development
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.