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Browsing by Author "Shahbazkia, Hamid Reza"

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  • A user-friendly software to easily count Anopheles egg batches
    Publication . Mollahosseini, Ali; Rossignol, Marie; Pennetier, Cedric; Cohuet, Anna; Dos Anjos, António; Chandre, Fabrice; Shahbazkia, Hamid Reza
    Background: Studies on malaria vector ecology and development/evaluation of vector control strategies often require measures of mosquito life history traits. Assessing the fecundity of malaria vectors can be carried out by counting eggs laid by Anopheles females. However, manually counting the eggs is time consuming, tedious, and error prone. Methods: In this paper we present a newly developed software for high precision automatic egg counting. The software written in the Java programming language proposes a user-friendly interface and a complete online manual. It allows the inspection of results by the operator and includes proper tools for manual corrections. The user can in fact correct any details on the acquired results by a mouse click. Time saving is significant and errors due to loss of concentration are avoided. Results: The software was tested over 16 randomly chosen images from 2 different experiments. The results show that the proposed automatic method produces results that are close to the ground truth. Conclusions: The proposed approaches demonstrated a very high level of robustness. The adoption of the proposed software package will save many hours of labor to the bench scientist. The software needs no particular configuration and is freely available for download on: http://w3.ualg.pt/(similar to)hshah/eggcounter/.
    2012-06Journal article Open access Show more
  • A comprehensive comparative study of quick invariant signature (QIS), dynamic time warping (DTW), and hybrid QIS + DTW for time series analysis
    Publication . Shahbazkia, Hamid Reza; Khosravani, Hamid Reza; Pulatov, Alisher; Hajimani, Elmira; Kiazadeh, Mahsa
    This study presents a comprehensive evaluation of the quick invariant signature (QIS), dynamic time warping (DTW), and a novel hybrid QIS + DTW approach for time series analysis. QIS, a translation and rotation invariant shape descriptor, and DTW, a widely used alignment technique, were tested individually and in combination across various datasets, including ECG5000, seismic data, and synthetic signals. Our hybrid method was designed to embed the structural representation of the QIS with the temporal alignment capabilities of DTW. This hybrid method achieved a performance of up to 93% classification accuracy on ECG5000, outperforming DTW alone (86%) and a standard MLP classifier in noisy or low-data conditions. These findings confirm that integrating structural invariance (QIS) with temporal alignment (DTW) yields superior robustness to noise and time compression artifacts. We recommend adopting hybrid QIS + DTW, particularly for applications in biomedical signal monitoring and earthquake detection, where real-time analysis and minimal labeled data are critical. The proposed hybrid approach does not require extensive training, making it suitable for resource-constrained scenarios.
    2025-03-19Journal article Open access Show more