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Object recognition system using KNN algorithm

 Department: Computer Science  
 By: usericon MIke_Tech_World  

 Project ID: 9675
   Rating:  (5.0) votes: 1
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   Price:₦5000
Abstract
An introduction to a new model for object recognition that uses sophisticated deep learning models (ideally suited for precisely classifying and identifying objects within an image). In this architecture, the system takes images as input and uses a KNN method to pass them through multiple layers in order to extract important features and patterns. Model parameters are adjusted across multiple epochs, with a variety of challenges such as data imbalance and overfitting along the way. The main technologies used are TensorFlow and Keras, aided by high-performance GPU resources to improve computing performance. With a simple and accessible interface, users can upload pictures as input data and get feedback on the recognized objects almost immediately. Through extensive testing, high accuracy rates are reported on a number of object categories, which demonstrate the potential for practical imagery applications. The functional low-cost differentiators used in this study inspire computers to distinguish between the same but distinctly different pixel-based images, paving the way for an object recognition framework that holds many implications in education, robotics and other aspects of life requiring visual input. Expanding into transfer learning, as well as real-time applications, are two processes that will work to augment this system in the future....
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