Image Recognition Final Year Projects with Source Code

Byadmin Final Year Projects

Image Recognition Final Year Projects for BE, BTech, ME, MSc, MCA and MTech final year engineering students. These Image Recognition projects give practical experience and help complete final-year submissions. All projects follow IEEE standards and each project includes source code, project thesis report, presentation, project execution and explanation.

Image Recognition Final Year Projects

  1. A CNN-OSELM Multi-Layer Fusion Network With Attention Mechanism for Fish Disease Recognition in Aquaculture
    This project helps identify diseases in fish using computer analysis of underwater images. It improves the accuracy of detection even when images are unclear. The system focuses on the important parts of the fish and learns quickly from new images. It can support farmers in keeping fish healthy and improving production.
  2. Data Augmentation Based on Generative Adversarial Networks for Endoscopic Image Classification
    This project aims to help doctors detect digestive system diseases more easily using computer-based image analysis. The system trains several deep learning models to automatically classify diseases from endoscopy images. It also creates extra training images using generative models to improve accuracy. The final model shows strong and safe performance, reducing the workload on medical staff.
  3. A Deep Learning-Based Experiment on Forest Wildfire Detection in Machine Vision Course
    This project focuses on detecting forest wildfires using artificial intelligence and image processing. It splits the problem into two parts: identifying images with wildfires and locating the wildfire areas in the images. The researchers developed new algorithms that use machine learning and deep learning, achieving high accuracy. The system is designed to be practical for students, helping them learn while producing reliable wildfire detection results.
  4. End-To-End Deep-Learning-Based Tamil Handwritten Document Recognition and Classification Model
    This project focuses on automatically reading Tamil handwritten text and converting it into digital text. It uses deep learning to first improve image quality and then separate lines and words. A MobileNet-based model extracts features, and a BiGRU model with optimization identifies each character. Tests show it can recognize Tamil handwriting accurately, achieving nearly 98.5% accuracy.
  5. Intelligent Deployment Solution for Tabling Adapting Deep Learning
    This project develops a smart system to improve mineral processing. It uses deep learning to analyze images and identify features of mineral ore belts. Then, it predicts how operating conditions affect these minerals using an advanced regression model. The system makes processing faster and more accurate, offering new possibilities for research.
  6. Research on Asparagus Recognition Based on Deep Learning
    This project focuses on making asparagus farming faster and more efficient. It uses a computer program to quickly detect asparagus plants for mechanized harvesting. The program is accurate and works well even with interference. This approach helps reduce labor costs and supports modern, large-scale farming.
  7. STGL-GCN SpatialTemporal Mixing of Global and Local Self-Attention Graph Convolutional Networks for Human Action Recognition
    This project focuses on recognizing human actions using skeleton data from videos. The method looks at both local and global connections between body joints to better understand movements. It uses a special neural network that learns which joint connections are most important for each action. Tests show it can accurately identify different human actions.
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How We Help You with Image Recognition Projects

At Final Year Projects, we provide complete guidance for Image Recognition IEEE projects for BE, BTech, ME, MSc, MCA and MTech students. We assist at every step from topic selection to coding, report writing, and result analysis.

Our team has over 10 years of experience guiding students in Computer Science, Electronics, Electrical, and other engineering domains. We support students across India, including Hyderabad, Mumbai, Bangalore, Chennai, Pune, Delhi, Ahmedabad, Kolkata, Jaipur and Surat. International students in the USA, Canada, UK, Singapore, Australia, Malaysia, and Thailand also benefit from our expert guidance.

Image Recognition Project Synopsis & Presentation

Final Year Projects helps prepare Image Recognition project synopsis, including problem statement, objectives, existing system, disadvantages, proposed system, advantages and research motivation. We provide PPT slides, tutorials, and full documentation for presentations.

Image Recognition Project Thesis Writing

Final Year Projects provides thesis writing services for Image Recognition projects. We help BE, BTech, ME, MSc, MCA and MTech students complete their final year project work efficiently.

All theses are checked with plagiarism check tools to guarantee originality and quality. Fast-track services are available for urgent submissions. Hundreds of students have successfully completed their projects and theses with our support.

Image Recognition Research Paper Support

We offer complete support for Image Recognition research papers. Services include writing, editing, and proofreading for journals and conferences.

We accept Word, RTF, and LaTeX formats. Every paper is reviewed to meet IEEE and publication standards, improving acceptance chances. Our guidance ensures that students produce high-quality, publication-ready research papers.

Reach out to Final Year Projects for expert guidance on Image Recognition projects. Get support for coding, reports, theses, and research publications. Contact us via email, phone, or website form and start your project with confidence.

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