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Exploring Low Cost Laser Sensors to Identify Flying Insect Species - Evaluation of Machine Learning and Signal Processing Methods.

, , , , and . Journal of Intelligent and Robotic Systems, 80 (Supplement-1): 313-330 (2015)

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A Comparison of Methods for Rule Subset Selection Applied to Associative Classification., , , and . Inteligencia Artif., 10 (32): 29-35 (2006)Effective insect recognition using a stacked autoencoder with maximum correntropy criterion., , , , , and . IJCNN, page 1-7. IEEE, (2015)SIGKDD demo: sensors and software to allow computational entomology, an emerging application of data mining., , , and . KDD, page 761-764. ACM, (2011)Applying One-Sided Selection to Unbalanced Datasets., , and . MICAI, volume 1793 of Lecture Notes in Computer Science, page 315-325. Springer, (2000)Adding Diversity to Rank Examples in Anytime Nearest Neighbor Classification., , and . ICMLA, page 129-134. IEEE, (2014)Unsupervised active learning techniques for labeling training sets: An experimental evaluation on sequential data., , , and . Intell. Data Anal., 21 (5): 1061-1095 (2017)A Complexity-Invariant Measure Based on Fractal Dimension for Time Series Classification., and . IJNCR, 3 (3): 59-73 (2012)An Open-Source Tool for Classification Models in Resource-Constrained Hardware., , and . CoRR, (2021)Time Series Prediction via Similarity Search: Exploring Invariances, Distance Measures and Ensemble Functions., , and . IEEE Access, (2022)Multi-view Semi-supervised Learning: An Approach to Obtain Different Views from Text Datasets., , and . LAPTEC, volume 132 of Frontiers in Artificial Intelligence and Applications, page 97-104. IOS Press, (2005)