What question did this study set out to answer?

The research aims to enhance the accuracy of object classification using a neural network based on coordinate features.

April 22, 2026Программные системы и вычислительные методыOpen Access

Analysis of a neural network for object classification using computer vision

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The research aims to enhance the accuracy of object classification using a neural network based on coordinate features.
Developed and modeled a neural network using a perceptron structure with specific input and output layers.
Utilized traditional methods such as forward propagation and gradient descent for training the neural network.
Conducted software implementation using Python in the PyCharm environment.
Demonstrated improved classification accuracy with minimized errors during testing.
Presented simulation results graphically, showing the loss function's behavior over training iterations.
Identified optimal parameters for the neural network related to different activation functions.

Authors

AMAnton Dmitrievich MihedBelarusian State Academy of Telecommunications

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Implication

Analyses the performance of a neural network in classifying objects based on their coordinates, suggesting improved accuracy in video surveillance systems.

Cite This Study

Anton Dmitrievich Mihed (2026) studied this question.

synapsesocial.com/papers/69e8656e6e0dea528dde9fa6 https://doi.org/10.7256/2454-0714.2026.1.78026

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Implication

Analyses the performance of a neural network in classifying objects based on their coordinates, suggesting improved accuracy in video surveillance systems.

Analysis of a neural network for object classification using computer vision

Key Points

Discussion

Implication

Cite This Study

Analysis of a neural network for object classification using computer vision

Key Points

Discussion

Implication

Cite This Study

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