Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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    Efficient Traffic Signboard Recognition System Using Convolutional Networks
    (Springer, 2020) Mothukuri, S.K.P.; Tejas, R.; Patil, S.; Darshan, V.; Koolagudi, S.G.
    In this paper, a smart automatic traffic sign recognition system is proposed. This signboard recognition system plays a vital role in the automated driving system of transport vehicles. The model is built based on convolutional neural network. The German Traffic Sign Detection Benchmark (GTSDB), a standard open-source segmented image dataset with forty-three different signboard classes is considered for experimentation. Implementation of the system is highly focused on processing speed and classification accuracy. These aspects are concentrated, such that the built model is suitable for real-time automated driving systems. Similar experiments are carried in comparison with the pre-trained convolution models. The performance of the proposed model is better in the aspects of fast responsive time. © Springer Nature Singapore Pte Ltd. 2020.
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    FASE Module Enabled Recognition of Individuals Using Distinct Gait Patterns
    (Institute of Electrical and Electronics Engineers Inc., 2024) Anusha, R.; Jaidhar, C.D.
    Extensive research has been conducted on gait, the walking pattern, and multiple methods have been created to utilize it as a biometric for identifying individuals. Nevertheless, there has been limited exploration of identifying individuals in running videos. A novel method is introduced in the paper that extends the feature-based approach to recognize individuals by their running patterns. The gait recognition performance is boosted in this work through the introduction of the Feature Analysis and Sample Elimination (FASE) module, which selects significant data samples using cluster formation, analysis, and elimination. Later on, the assignment of a testing sample to the training sample is achieved through the use of the proposed classification method. The experiments utilize the KTH, OU-ISIR A, and Weizmann databases. The obtained experimental results showcase the effectiveness of the proposed method. © 2024 IEEE.