1 |
Tensorflow, "Object detection model zoo", 2020. https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md
|
2 |
L. Vuegen, B. V. D. Broeck, P. Karsmakers, J. F. Gemmeke, B. Vanrumste, H. V. Hamme, "An mfcc-gmm approach for event detection and classification", IEEE AASP Challenge on Detection and Classification of Acoustic Scenes and Events, pp.1-3, 2013. http://c4dm.eecs.qmul.ac.uk/sceneseventschallenge/abstracts/OL/VVK.pdf
|
3 |
S. Sahoo, A. Routray, "Detecting Aggression in Voice Using Inverse Filtered Speech Features", IEEE Transactions on Affective Computing, Vol. 9, No. 2, pp. 217-226, 2018. https://doi.org/10.1109/TAFFC.2016.2615607
DOI
|
4 |
J. Lee, H. Tseng, "Development of an Enhanced Threshold-Based Fall Detection System Using Smartphones with Built-In Accelerometers," in IEEE Sensors Journal, Vol. 19, No. 18, pp. 8293-8302, 2019. https://doi.org/10.1109/JSEN.2019.2918690
DOI
|
5 |
A. Jalal, M. A. K. Quaid, M. A. Sidduqi, "A Triaxial Acceleration-based Human Motion Detection for Ambient Smart Home System", 16th International Bhurban Conference on Applied Sciences and Technology, pp. 353-358, 2019. https://doi.org/10.1109/IBCAST.2019.8667183
|
6 |
Guto LS, Patricia TE, Kayo HDCM, Elisson DSR, lvanovitch S, Theo L, "Accelerometer-based human fall detection using convolutional neural networks", Sensors (Basel), Vol. 19, No.7, pp. 1-12, 2019. https://doi.org/10.3390/s19071644
|
7 |
C. Srivastava, S. Singh, A. P. Singh, "IoT-enabled air monitoring system", Intelligent Systems, Technologies and Applications, Vol. 910, pp. 173-180, 2020. https://doi.org/10.1007/978-981-13-6095-4_13
DOI
|
8 |
L. A. A. Cruza, M. T. T. Griñoa, T. M. V. Tungola, J. T. Bautista, "Development of a Low-Cost Air Quality Data Acquisition IoT-based System using Arduino Leonardo", International Journal of Engineering and Manufacturing, Vol. 9, No. 3, pp. 1-18, 2019. https://doi.org/10.5815/ijem.2019.03.01
|
9 |
J. Jung, J. Ahn, "Intelligent user pattern recognition based on vision, audio and activity for abnormal event detections of single households", Journal of The Korea Society of Computer and Information, Vol. 24, No. 5, pp. 59-66, 2019. https://doi.org/10.9708/jksci.2019.24.05.059
DOI
|
10 |
J. Jung, J. Ahn, "Intelligent abnormal event detection algorithm for single households at home via daily audio and vision patterns", Journal of Internet Computing and Services, Vol. 20, No. 1, pp. 77-86, 2019. https://doi.org/10.7472/jksii.2019.20.1.77
DOI
|
11 |
J. Song, J. Jung, J. Ahn, "Intelligent pattern recognition algorithms based on dust, vision and activity sensors for user unusual event detection", Journal of The Korea Society of Computer and Information, Vol. 24, No. 8, pp. 95-103, 2019. https://doi.org/10.9708/jksci.2019.24.08.095
DOI
|
12 |
C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, Z. Wojna, "Rethinking the inception architecture for computer vision", IEEE Conference on Computer Vision and Pattern Recognition, pp. 2818-2826, 2016. https://doi.org/10.1109/CVPR.2016.308
|
13 |
Dementianews, "The number of single-person households in the world has skyrocketed. Familyoriented care policy for the elderly 'hourly wage'", https://www.dementianews.co.kr/news/articleView.html?idxno=2397
|
14 |
S. Ren, K. He, R. Girshick, J. Sun, "Faster R-CNN: towards real-time object detection with region proposal networks", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 39, No. 6, pp. 1137-1149, 2017. https://doi.org/10.1109/TPAMI.2016.2577031
DOI
|