Video Scene Location Recognition Using AI: Conclusion and Future Research

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Video Scene Location Recognition Using AI: Conclusion and Future Research
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This study explores scene recognition in TV series using neural networks, tested on The Big Bang Theory, with various layers like LSTM and pooling methods.

Authors: Lukáš Korel, Faculty of Information Technology, Czech Technical University, Prague, Czech Republic; Petr Pulc, Faculty of Information Technology, Czech Technical University, Prague, Czech Republic; Jirí Tumpach, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic; Martin Holena, Institute of Computer Science, Academy of Sciences of the Czech Republic, Prague, Czech Republic.

Conference on Computer Vision and Pattern Recognition , pp. 770–778 Sudha V., Ganeshbabu T. R.: A Convolutional Neural Network Classifier VGG-19 Architecture for Lesion Detection and Grading in Diabetic Retinopathy Based on Deep Learning. http://www.techscience.com/cmc/v66n1/40483 Computers, Materials & Continua , pp. 827–842 Zhou B., Lapedriza A., Khosla A., Oliva A., Torralba A.: Places: A 10 Million Image Database for Scene Recognition.

pp. 850-–855 Benavoli A., Corani G., Mangili F.: Should We Really Use Post-Hoc Tests Based on Mean-Ranks? Journal of Machine Learning Research 17 , pp. 1–10 García S., Herrera F.: An Extension on "Statistical Comparisons of Classifiers over Multiple Data Sets" for all Pairwise Comparisons Journal of Machine Learning Research 9 , pp. 2677–2694 Graves, A.: Supervised Sequence Labelling with Recurrent Neural Networks. Springer Kaiming H., Xiangyu Z., Shaoqing R., Jian S.

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