1 |
Song, X., E. A. M, Bokkers., P. P. J, van der Tol., P. G, Koerkamp., S, Van Mourik., "Automated body weight prediction of dairy cows using 3-dimensional vision", Journal of Dairy Science, Vol.101, No.5, (2018), 4448-4459
DOI
|
2 |
Zhou, J., X, Hong., F, Su., G, Zhao., "Recurrent convolutional neural network regression for continuous pain intensity estimation in video", IEEE conference on computer vision and pattern recognition workshops, (2016), 84-92
|
3 |
Pouladzadeh, P., S, Shirmohammadi., R, Al-Maghrabi., "Measuring calorie and nutrition from food image", IEEE Trans. Instrum. Meas, Vol.63, No.8, (2014), 1947-1956
DOI
|
4 |
Pet Industry Market Size, Trends Ownership Statistics, American Pet Products Association, 2021. Available at https://www.americanpetproducts.org/press_industrytrends.asp (Accessed 2022.03.02)
|
5 |
Lee, J., Suh, B., Y. Kwon, "A Study on the impact of artificial intelligence on decision making: focusing on human-AI collaboration and decision-maker's personality trait." Journal of Intelligence and Information Systems, Vol. 27, No. 3, (2021), 231-252.
DOI
|
6 |
Wadhawni, P., S, Ganka., Pet Tech Market, Global Market Insights, 2021, Available at https://www.gminsights.com/industry-analysis/pet-tech-market (Accessed 2022.03.02)
|
7 |
Dehais, J., M, Anthimopoulos., S, Shevchik., S, Mougiakakou., "Two-view 3D reconstruction for food volume estimation", IEEE, Vol.19, No.5, (2017), 1090-1099
|
8 |
Geirhos, R., P, Rubisch., C, Michaelis., M, Bethge., F. A, Wichmann., W, Brendel., "ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness", arXiv preprint arXiv, 1811.12231, (2018)
|
9 |
Jiang, M., G, Guo., "Body weight analysis from human body images", IEEE Transactions on Information Forensics and Security, Vol.14, No.10, (2019), 2676-2688
DOI
|
10 |
Koley, S., S, Srimani., D, Nandy., P, Pal., S, Biswas., I, Sarkar., "Smart Pet Feeder", In Journal of Physics: Conference Series, Vol.1797, No.1, (2021), 12018
|
11 |
Rajpurkar, P., J, Irvin., K, Zhu., B, Yang., H, Mehta., T, Duan., A.Y, Ng., "Chexnet: Radiologist-level pneumonia detection on chest x-rays with deep learning", arXiv preprint arXiv, 1711.05225, (2017)
|
12 |
Seo, Y., K.S. Shin, "Business application of convolutional neural networks for apparel classification using runway image.", Journal of Intelligence and Information Systems, Vol. 24, No. 3, (2018), 1-19.
DOI
|
13 |
Subhi, M. A., S. H. M, Ali., A. G, Ismail., M, Othman., "Food volume estimation based on stereo image analysis", IEEE Instrumentation & Measurement Magazine, Vol.21, No.6, (2018), 36-43
DOI
|
14 |
Mortensen, A. K., P, Lisouski., P, Ahrendt., "Weight prediction of broiler chickens using 3D computer vision", Computers and Electronics in Agriculture, Vol.123, (2016), 319-326
DOI
|
15 |
Deloitte., "Consumption Trends Driven by COVID-19", Deloitte Insights, No.17, (2021), 50-54
|
16 |
Babu, B. R., P.P Kumar., P.G Kuppusamy., "Arduino Mega based PET feeding automation", IOSR Journal of Electronics and Communication Engineering, Vol.14, No.4, (2019), 13-16
|
17 |
Buayai, P., P, Kullapapruk., L, Carson., K.R. Saikaew., "Semi-automatic pig weight estimation using digital image analysis", Applied Engineering in Agriculture, Vol. 35, No.4, (2019), 521-534
DOI
|
18 |
Cominotte, A., A. F. A, Fernandes., J. R. R, Dorea., G. J. M, Rosa., M. M, Ladeira., E. H. C. B, van Cleef., O. M, Neto.,"Automated computer vision system to predict body weight and average daily gain in beef cattle during growing and finishing phases", Livestock Science, Vol.232, No.103904, (2020)
|
19 |
Fernandes, A. F., E. M, Turra., E. R. de Alvarenga., T. L. Passafaro., F. B, Lopes., G. F, Alves., G. J, Rosa, "Deep Learning image segmentation for extraction of fish body measurements and prediction of body weight and carcass traits in Nile tilapia", Computers and electronics in agriculture, Vol. 170, No.105274, (2020)
|
20 |
Xue, Y., N, Ray., J, Hugh., G, Bigras., "Cell counting by regression using convolutional neural network", In European Conference on Computer Vision, (2016), 274-290
|
21 |
HosseinNia, S.H., I, Tejado., B.M, Vinagre., "Fractional-order reset control: Application to a servomotor", Mechatronics, Vol.23, No.7, (2013), 781-788
DOI
|
22 |
Gjergji, M., V, de Moraes Weber., L. O. C, Silva., R, da Costa Gomes., T. L. A. C, De Araujo., H, Pistori., M, Alvarez., "Deep learning techniques for beef cattle body weight prediction", International Joint Conference on Neural Networks (IJCNN), (2020), 1-8
|
23 |
Kashiha, M., C, Bahr., S, Ott., C. P, Moons., T. A, Niewold., F. O, Odberg., D, Berckmans., "Automatic weight estimation of individual pigs using image analysis", Computers and Electronics in Agriculture, Vol.107, (2014), 38-44
DOI
|
24 |
Kienzle, E., R, Bergler., A, Mandernach., "A comparison of the feeding behavior and the human-animal relationship in owners of normal and obese dogs", The Journal of nutrition, Vol.128, No.12, (1998), 2779S-2782S
DOI
|
25 |
Konovalov, D. A., A, Saleh., D. B, Efremova., J. A, Domingos., D. R, Jerry., "Automatic weight estimation of harvested fish from images", Digital Image Computing: Techniques and Applications(DICTA), (2019), 1-7
|
26 |
Liu, R., "Automatic Pet Feeder based on Single Chip Microcomputer", In Journal of Physics: Conference Series, Vol. 2037, No. 1, (2021), 12104
|
27 |
Lee, M. S., H. Ahn, "A time series graph based convolutional neural network model for effective input variable pattern learning: Application to the prediction of stock market." Journal of Intelligence and Information Systems, Vol. 24, No. 1, (2018) 167-181.
DOI
|
28 |
Malmanger, E., Why Is My Dog Not Eating?, PetMD, 2021, Available at https://www.petmd.com/dog/symptoms/why-my-dog-not-eating (Accessed 2022.03.02)
|
29 |
Srivastava, N., G, Hinton., A, Krizhevsky., I, Sutskever., R, Salakhutdinov., "Dropout: a simple way to prevent neural networks from overfitting", The journal of machine learning research, Vol.15, No.1, (2014), 1929-1958
|
30 |
Shin, H., J, Kim., "A Study on the Development of Wearable Products Applied to PetTech Service Using IoT and AI Technolog", The Journal of Korean Society of Design Culture, Vol.26, No.1, (2020), 261-272
DOI
|
31 |
Puri, M., Z, Zhu., Q, Yu., A, Divakaran., H, Sawhney., "Recognition and volume estimation of food intake using a mobile device", Workshop on Applications of Computer Vision (WACV), (2009), 1-8
|
32 |
Pyo, J., H, Duan., S, Baek., M.S, Kim., T, Jeon., Y.S, Kwon., K.H, Cho., "A convolutional neural network regression for quantifying cyanobacteria using hyperspectral imagery", Remote Sensing of Environment, Vol.233, No. 111350, (2019)
|
33 |
Zhu, F., M, Bosch., C.J, Boushey., E.J, Delp., "An image analysis system for dietary assessment and evaluation", IEEE Int. Conf. on Image Processing, (2010), 1853-1856
|
34 |
Razzaki, S., A, Baker., Y, Perov., K, Middleton., J, Baxter., D, Mullarkey., S, Johri., "A comparative study of artificial intelligence and human doctors for the purpose of triage and diagnosis", arXiv preprint arXiv, 1806.10698, (2018)
|
35 |
Rahman, M.H., "Food volume estimation in a mobile phone based dietary assessment system", Conf. on Signal Image Technology and Internet Based Systems (SITIS), (2012), 988-995
|
36 |
Tessema, G.B., T.A, Worku., Z.B, Tessema., "Programmable Pet Feeder", International Journal of Scientific Engineering and Research (IJSER), Vol.3, No.11, (2015), 99-104
|
37 |
Vania, K. Karyono., I.H.T, Nugroho., "Smart dog feeder design using wireless communication, MQTT and Android client", International Conference on Computer, Control, Informatics and its Applications (IC3INA), (2016), 191-196
|
38 |
Xu, C., Y.K.N, He., A, Parra., C, Boushey., E, Delp., "Image-based food volume estimation", 5th Int. Workshop on Multimedia for Cooking and Eating Activities, (2013), 75-80
|