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@article{193727,
        author = {E D Pavan Kumar and C. Venkata Ramana and Y Pradeep Reddy and K Pavan Sankar and A Vinay and B Saiprem},
        title = {Automated AI-Powered Fruit Identification using Convolutional Neural Network},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {1621-1627},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=193727},
        abstract = {Sophisticated mechanism that has the ability to scan photos of fruits and determine the type of fruit each photo depicts. Artificial intelligence-based software and applications such as deep learning, which is a kind of crash course in fruit recognition by the Machine learning model. The process here trains the ML Model we explicitly described the Model by the agent of an application with PEAS and the task environment of an application with the 6 dimensions which with time it becomes extremely good at identifying the differences and similarities between, say, a banana and a grape. Another method that we employed was pattern recognition whereby the computer focuses on certain features such as the color of the fruit, shape, size and texture. Going through several challenges to recognize the kind of fruit in the picture in automatic recognition. The color, the texture, and the shape of numerous types of fruits are those affected by the variety of images. Convolutional Neural Network (CNN) Algorithm was better at detecting pictures of fruits in all aspects, including accuracy, as well as it is a much faster method to apply to new fruits, when compared to regular support-vector-machine-based methods with handcrafted features. Combining deep learning and pattern recognition algorithms like Convolutional Neural Network Algorithm our system has achieved an accuracy of 84 percent, meaning that our system successfully identified various types of fruits based on the pictures and this shows the strength and the ability of our algorithm. Our project objective is to develop a tool that can identify a wide variety of fruits in the form of photos in a short time and with accuracy, which would help in the eventuality of applications such as sorting fruits at a grocery store or assist individuals in learning about various types of fruit through the use of Convolutional Neural Network Algorithm. It is not just a question of training a computer to identify fruits and this is the ability to make technology understand and communicate with the world in a manner that is useful to us.},
        keywords = {Deep learning, Pattern recognition, fruit detection, computer vision, machine learning, Convolutional Neural Networks},
        month = {March},
        }