Amraei, S., Abdanan Mehdizadeh, S. and Salari, S. (2017). Broiler weight estimation based on machine vision and artificial neural network. British PoultryScience. 58(2). http://dx.doi.org/10.1080/00071668.2016.1259530
Bailey, D.G., Mercer, K.A., Plaw,C., Ball,R., and Barraclough, H.(2004). High Speed Weight Estimation by Image Analysis. Proceedings of the 2004 New Zealand National Conference on Non Destructive Testing June 27-29, 2004, Palmerston North, New Zealand.
Banerjee, K., Jasrai, Y.T., and Jain, N.K .(2012). An Accessible and Accurate Image Analysis for Root Length and Leaf Area Estimation: A Case Application to Azadirachta indica Seedlings. American-Eurasian Journal of agricultural and environmental sciences. 12: 64-76.
Bazlur, M.d., and Mollah,R .(2010). Digital image analysis to estimate the live weight of broiler. Computers and Electronics in Agriculture. 72(1): 48-52.
Bhuvaneshwari,M. L.M. and Palanivelu M.S. (2015). Improvement in detection of chicken egg fertility using image processing teqniques. International Journal On Engineering Technology and Sciences. 2(4):64-67.
Chmiel,M., Sowi_nski,M., Dasiewicz,K.2011. Application of computer vision systems for estimation of fat content in poultry meat. Food Control. 22 : 1424-1427.
Chora,R.S.(2007). Image Feature Extraction Techniques and Their Applications for CBIR and Biometrics Systems. International Journal of Biology and Biomedical Engineering. 1(1): 6-16.
Dehrouyeh, M.H. , Omid, M. , Ahmadi, H., Mohtasebi, S.S., and Jamzad, M.(2005). Grading and Quality Inspection of Defected Eggs Using Machine Vision. International Journal of Advance Science and Technology. 16: 43-50.
De Wet, L., Vranken, E., Chedad, A., Aerts, J.M., Ceunen, J., Berckmans, D.(2003). Computer-assisted image analysis to quantify daily growth rates of broiler chickens. British Poultry Science. 44(4):524-32.
Forbes,K.(2000). Volume Estimation of Fruit from Digital Profile Images. A dissertation submitted to the Department of Electrical Engineering, University of Cape Town, in fulfilment of the requirements for the degree of Master of Science in Engineering
Gonzalez, R., and Woods, R. E.(2002). Digital Image Processing. 2nd eddition .Addison-Wesley.
Goyal, S.(2013). Predicting properties of cereals using artificial neural networks: A review. Scientific Journal of Crop Science. 2: 95-115.
Hao,M., Yu,H., and Li,D.(2016). The Measurement of Fish Size by Machine Vision-A Review. IFIP International Federation for Information Processing. IFIP AICT. 479:15–32, DOI: 10.1007/978-3-319-48354-2_2.
Junior, Y.T., Silva, E., Junior, R.A.B., Lopes, M.A., Damascene, F.A., Silva, G.C.D.A.E.(2011). Digital Surface Area Assessment of Broiler Chickens. Engenharia Agrícola, Jabotcabal. 31:468-476.
Khojastehkey,M. Aslaminejad ,A.A. shariati,M.M. and Dianat,R.(2015). Body size estimation of new born lambs using image processing and its effect on the genetic gain of a simulated population. Journal of Applied Animal Research.44(1):326-330. DOI: 10.1080/09712119.2015.1031789.
Negretti ,P., Bianconi , G. , Bartocci,S. , and Terramoccia, S.(2007). Lateral Trunk Surface as a new parameter to estimate live body weight by Visual Image Analysis. Italian Journal of Animal Science. 6:1223-1225.
Onder, H., Arl, A., Ocak, S., Eker, S., and Tufekci, H.(2011).Use of Image Analysis in Animal Science. Journal of Information Technology in Agriculture. 1:1-4.
Phyu, T.N.(2009). Survey of Classification Techniques in Data Mining. Proceedings of the International MultiConference of Engineers and Computer Scientists, March 18 - 20, Hong Kong.
Souza, C. F., Mogami, C.A., Ferreira,I.F., Pinto,F.A.C., Inoue,K.R.A., Júnior.H.S.(2013). Methodology for determination of body mass gain of broilers in commercial aviaries via digital image analysis. American Society of Agricultural and Biological Engineers, annual international meeting, Kansas city,Missouri,USA/ Doi: http://dx.doi.org/10.13031/aim.20131620477 .
Stajnko, D., Vindiš,P., Janžekovič,M., and Brus,M.(2010). Non Invasive Estimating of Cattle Live Weight Using Thermal Imaging. New Trends in Technologies: Control, Management, Computational Intelligence and Network Systems, Meng Joo Er (Ed.), ISBN: 978-953-307-213-5.438 pages. Chapter 13.
Tasdemir,S., Urkmez,A., and Inal,S.(2011). A fuzzy rule-based system for predicting the live weight of Holstein cows whose body dimensions were determined by image analysis. Turkish Journal of Electronic Engineering and Computer Science. 19(4):689-703.
Wang, Y., Yang,W., Winter,P., and Walker,L.(2008). Walk-through weighing of pigs using machine vision and an artificial neural network. Biosystems Engineering. 100:117–125.
Yudkowsky,E.( 2008). Artificial Intelligence as a Positive and Negative Factor in Global Risk, edited by Nick Bostrom and Milan M. Ćirković, 308–345. New York: Oxford University Press.