Image Dataset Final Year Projects with Source Code
Image Dataset Final Year Projects for BE, BTech, ME, MSc, MCA and MTech final year engineering students. These Image Dataset 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 Dataset Final Year Projects
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FieldPlant A Dataset of Field Plant Images for Plant Disease Detection and Classification With Deep Learning
This project focuses on improving the detection of plant diseases using images taken directly from farms. Researchers created a new dataset called FieldPlant, with over 5,000 real-field images carefully labeled by plant experts. They tested modern deep learning models on this dataset and found that these models performed better than when trained on previous datasets. The goal is to help farmers detect diseases more accurately and reduce food waste. -
GARL-Net Graph Based Adaptive Regularized Learning Deep Network for Breast Cancer Classification
This project focuses on improving breast cancer detection using computer-based image analysis. The researchers developed a new deep learning method called GARL-Net that can learn more efficiently from large and uneven image datasets. It uses advanced techniques to reduce errors in classification and improve accuracy. Tests on popular breast cancer image datasets showed very high accuracy, precision, and recall, outperforming existing methods. -
Rearranging Pixels is a Powerful Black-Box Attack for RGB and Infrared Deep Learning Models
This project studies how neural networks for image recognition can be tricked by specially designed attacks. The researchers created two new attack methods and tested them on normal and infrared images. They also showed that using these attacks in training can make models stronger and more reliable. Finally, they explored if attacks in one type of image can affect another type without extra adjustments. -
Shrimpseed Net Counting of Shrimp Seed Using Deep Learning on Smartphones for Aquaculture
This project focuses on creating a smart system to count shrimp seeds automatically. Instead of manual counting, which is slow and error-prone, the system uses a modified neural network called Shrimpseed_Net. It works on smartphones, allowing users to take or upload a picture of shrimp seeds and get an accurate count in seconds. The system achieves high accuracy and can help modernize and improve efficiency in shrimp farming.
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At Final Year Projects, we provide complete guidance for Image Dataset 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.
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Image Dataset Project Synopsis & Presentation
Final Year Projects helps prepare Image Dataset 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 Dataset Project Thesis Writing
Final Year Projects provides thesis writing services for Image Dataset 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 Dataset Research Paper Support
We offer complete support for Image Dataset 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.
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