Number	Title	Reference
A1	Investigation into the production and conformation traits associated with clinical mastitis using artificial neural networks	[29]
A2	Identifying Health Status in Grazing Dairy Cows from Milk Mid-Infrared Spectroscopy by Using Machine Learning Methods	[30]
A3	Comparative efficiency of artificial neural networks and multiple linear regression analysis for prediction of first lactation 305-day milk yield in Sahiwal cattle	[15]
A4	A computerized mastitis decision aid using farm-based records: An artificial neural network approach	[31]
A5	Comparison of modeling techniques for milk-production forecasting	[19]
A6	Mastitis detection in dairy cows by application of neural networks	[32]
A7	Multiple Country Approach to Improve the Test-Day Prediction of Dairy Cows’ Dry Matter Intake	[33]
A8	Artificial insemination for milk production in India: A statistical insight	[18]
A9	Classification and prediction of milk yield level for Holstein Friesian cattle using parametric and non-parametric statistical classification models	[34]
A10	Improving farm decisions: The application of data engineering techniques to manage data streams from contemporary dairy operations	[35]
A11	COMPARISON OF ANALYSIS TECHNIQUES FOR ONLINE DETECTION OF CLINICAL MASTITIS	[36]
A12	Detection of difficult calvings in dairy cows using neural classifier	[37]
A13	Use of neural networks to detect minor and major pathogens that cause bovine mastitis	[38]
A14	Determination of Body Parts in Holstein Friesian Cows Comparing Neural Networks and K-Nearest Neighbour Classification	[39]
A15	Opportunistic Wireless Networking for Smart Dairy Farming	[20]
A16	Farming smarter with big data: Insights from the case of Australia’s national dairy herd milk recording scheme	[40]
A17	Prediction of first lactation 305-day milk yield in Karan Fries dairy cattle using ANN modeling	[41]
A18	Individual identification of dairy cows based on convolutional neural networks	[42]
A19	Artificial intelligence applied to a robotic dairy farm to model milk productivity and quality based on cow data and daily environmental parameters	[43]
A20	Classifying milk yield using deep neural network	[44]
A21	Application of a neural network to analyze on-line milking parlor data for the detection of clinical mastitis in dairy cows	[45]
A22	A cluster-graph model for herd characterization in dairy farms equipped with an automatic milking system	[46]
A23	Disease Diagnosis of Dairy Cow by Deep Learning Based on Knowledge Graph and Transfer Learning	[47]
A24	Deep cascaded convolutional models for cattle pose estimation	[48]
A25	A computer vision approach based on deep learning for the detection of dairy cows in free stall barn	[49]
A26	SmartHerd management: A microservices-based fog computing–assisted IoT platform towards data-driven smart dairy farming	[50]
A27	Detection of cows with insemination problems using selected classification models	[51]
A28	Improving dairy yield predictions through combined record classifiers and specialized artificial neural networks	[52]
A29	SocialCattle: IoT-based Mastitis Detection and Control through Social Cattle Behavior Sensing in Smart Farms	[53]
A30	Use of test-day records to predict first lactation 305-day milk yield using artificial neural network in Kenyan Holstein-Friesian dairy cows	[54]
A31	Comparison of artificial neural network and multiple linear regression for prediction of first lactation milk yield using early body weights in Sahiwal cattle	[16]
A32	Prediction of lifetime milk production using artificial neural network in Sahiwal cattle	[55]
A33	Detection of mastitis and its stage of progression by automatic milking systems using artificial neural networks	[56]
A34	Machine-learning-based calving prediction from activity, lying, and ruminating behaviors in dairy cattle	[57]
A35	The use of artificial neural networks for modeling rumen fill	[58]
A36	Biometric physiological responses from dairy cows measured by visible remote sensing are good predictors of milk productivity and quality through artificial intelligence	[59]
A37	Effects of data preprocessing on the performance of artificial neural networks for dairy yield prediction and cow culling classification	[60]
A38	Neural networks applied to a large biological database to analyze dairy breeding patterns	[61]
A39	Prediction of second parity milk yield of Kenyan Holstein-Friesian dairy cows on first parity information using neural network system and multiple linear regression methods	[62]
A40	Comparison of artificial neural network and K-means for clustering dairy cattle	[63]
A41	Leveraging latent representations for milk yield prediction and interpolation using deep learning	[64]
A42	Neural detection of mastitis from dairy herd improvement records	[65]
A43	Effects of learning parameters and data presentation on the performance of backpropagation networks for milk yield prediction	[66]
A44	Symposium review: Dairy Brain—Informing decisions on dairy farms using data analytics	[67]
A45	Prediction of cow performance with a connectionist model	[68]
A46	A comparison of neural network and multiple regression predictions for 305-day lactation yield using partial lactation records	[69]
A47	Application of neural network and adaptive neuro-fuzzy inference system to predict subclinical mastitis in dairy cattle	[70]
A48	Predictions of 305-day milk yield in Iranian Dairy cattle using test-day records by artificial neural network	[71]
A50	Estimating Heritabilities and Breeding Values for Real and Predicted Milk Production in Holstein Dairy Cows with Artificial Neural Network and Multiple Linear Regression Models	[72]
A51	Comparison of methods to predict feed intake and residual feed intake using behavioral and metabolite data in addition to classical performance variables	[73]
A52	Dynamic forecasting of individual cow milk yield in automatic milking systems	[74]
A53	Mining data from milk infrared spectroscopy to improve feed intake predictions in lactating dairy cows	[75]
A54	Fluctuations in milk yield are heritable and can be used as a resilience indicator to breed healthy cows	[76]
A55	Determination of factors affecting dairy cattle: a case study of Ardahan province using data-mining algorithms	[77]
A56	A comparison of 4 different machine learning algorithms to predict lactoferrin content in bovine milk from mid-infrared spectra	[78]
A57	Prediction of 305-day milk yield in Brown Swiss cattle using artificial neural networks	[79]
A58	Comparative study of feed-forward neuro-computing with multiple linear regression model for milk yield prediction in dairy cattle	[80]
A59	Prediction of second parity milk performance of dairy cows from first parity information using artificial neural network and multiple linear regression methods	[17]
A60	Adaptive cow movement detection using evolving spiking neural network models	[81]
A61	Ranking of environmental heat stressors for dairy cows using machine learning algorithms	[82]
A62	Tracking and analyzing social interactions in dairy cattle with real-time locating system and machine learning	[83]
A63	Machine learning-based fog computing assisted data-driven approach for early lameness detection in dairy cattle	[84]
A64	Detecting dairy cow behavior using vision technology	[85]
A65	Prediction of insemination outcomes in Holstein dairy cattle using alternative machine learning algorithms	[86]
A66	Body condition estimation on cows from depth images using Convolutional Neural Networks	[87]
A67	Comparison of forecast models of production of dairy cows combining animal and diet parameters	[88]
A68	Development of a recurrent neural networks-based calving prediction model using activity and behavioral data	[89]
A69	Using a CNN-LSTM for basic behavior detection of a single dairy cow in a complex environment	[90]
A70	An automatic model configuration and optimization system for milk production forecasting	[91]
A71	Predicting the milk yield curve of dairy cows in the subsequent lactation period using deep learning	[92]
A72	Short communication: Use of genomic and metabolic information as well as milk performance records for prediction of subclinical ketosis risk via artificial neural networks	[93]
A73	Prediction of FL 305 DMY from monthly part lactation milk yield records using artificial intelligence in Sahiwal cattle	[94]
A74	Lactation milk yield prediction in primiparous cows on a farm using the seasonal auto-regressive integrated moving average model, nonlinear autoregressive exogenous artificial neural networks, and Wood’s model	[95]
A75	Predicting bovine tuberculosis status of dairy cows from mid-infrared spectral data of milk using deep learning	[96]
A76	Artificial Neural Network versus Multiple Regression Analysis for Prediction of Lifetime Milk Production in Sahiwal Cattle	[97]
A77	Symposium review: Challenges and opportunities for evaluating and using the genetic potential of dairy cattle in the new era of sensor data from automation	[98]
A78	Milk production estimates using feed-forward artificial neural networks	[99]
A79	Prediction of second parity milk yield and fat percentage of dairy cows based on first parity information using neural network system	[100]
A80	Development of lifetime milk yield equation using artificial neural network in Holstein Friesian crossbred dairy cattle and comparison with multiple linear regression model	[101]
A81	Methods of predicting milk yield in dairy cows-Predictive capabilities of Wood’s lactation curve and artificial neural networks (ANNs)	[102]
A82	Predicting first test day milk yield of dairy heifers	[103]
A83	Empirical comparisons of feed-forward connectionist and conventional regression models for prediction of first lactation 305-day milk yield in Karan Fries dairy cows	[104]
A84	Development of neuro-fuzzifiers for qualitative analyses of milk yield	[105]
A85	Predicting mastitis in dairy cows using neural networks and generalized additive models: A comparison	[106]
A86	Machine-learning algorithms for predicting on-farm direct water and electricity consumption on pasture-based dairy farms	[107]
A87	Computer vision system for measuring individual cow feed intake using RGB-D camera and deep learning algorithms	[108]
A88	Lameness scoring system for dairy cows using force plates and artificial intelligence	[109]
A89	Now you see me: Convolutional neural network-based tracker for dairy cows	[110]
A90	An intelligent Edge-IoT platform for monitoring livestock and crops in a dairy farming scenario	[111]
A91	A machine learning-based decision aid for lameness in dairy herds using farm-based records	[112]
A92	Exploring machine learning algorithms for early prediction of clinical mastitis	[113]
A93	Expert system based on a fuzzy logic model for the analysis of the sustainable livestock production dynamic system	[114]
A94	Machine learning approaches for the prediction of lameness in dairy cows	[115]
A95	Mastitis detection with recurrent neural networks in farms using automated milking systems	[116]
A96	Comprehensive analysis of machine learning models for prediction of sub-clinical mastitis: Deep Learning and Gradient-Boosted Trees outperform other models	[117]
A97	Using decision trees to extract patterns for dairy culling management	[118]
A98	Decision-tree induction to detect clinical mastitis with automatic milking	[119]
A99	Automated prediction of mastitis infection patterns in dairy herds using machine learning	[120]
A100	Hierarchical pattern recognition in milking parameters predicts mastitis prevalence	[120]
A101	Comparison of data-driven mastitis detection methods	[121]
A102	Uncovering Patterns in Dairy Cow Behavior: A Deep Learning Approach with Tri-Axial Accelerometer Data	[122]
A103	An efficient multi-task convolutional neural network for dairy farm object detection and segmentation	[123]
A104	Risk prediction model of clinical mastitis in lactating dairy cows based on machine learning algorithms	[124]
A105	Conceptualizing a holistic smart dairy farming system	[125]
A106	Cows’ legs tracking and lameness detection in dairy cattle using video analysis and Siamese neural networks	[126]
A107	A stochastic animal life cycle simulation model for a whole dairy farm system model: Assessing the value of combined heifer and lactating dairy cow reproductive management programs	[127]
A108	Comparison of imputation methods for missing production data of dairy cattle	[128]
A109	The Use of Artificial Neural Networks for Prediction of Milk Productivity of Cows in Ukraine; [Ukrayna’da İneklerin Süt Verimliliğinin Tahmininde Yapay Sinir Ağlarının Kullanımı]	[129]
A110	Calf Posture Recognition Using Convolutional Neural Network	[130]
A111	Prediction of first lactation 305 days milk yield using artificial neural network in Murrah buffalo	[131]
A112	Fusion of RGB, optical flow, and skeleton features for the detection of lameness in dairy cows	[132]
A113	The relationship between dry period length and milk production of Holstein dairy cows in tropical climate: a machine learning approach	[133]
A114	Use of Machine Learning and IoT for Monitoring and Tracking of Livestock	[134]
A115	The Use of Multilayer Perceptron Artificial Neural Networks to Detect Dairy Cows at Risk of Ketosis	[135]
A116	Dairy Cow Behavior Recognition Using Computer Vision Techniques and CNN Networks	[136]
A117	A Deep Learning-based solution to Cattle Region Extraction for Lameness Detection	[137]
A118	Modeling and forecasting of milk production in different breeds in Turkey	[138]
A119	Facial Recognition of Dairy Cattle Based on Improved Convolutional Neural Network∗	[139]
A120	Comparison and Selection of Artificial Intelligence Technology in Predicting Milk Yield	[140]
A121	A Deep Learning Framework for Improving Lameness Identification in Dairy Cattle	[141]
A122	Research on Application Technology of 5G Internet of Things and Big Data in Dairy Farm	[142]
A123	Implementing artificial intelligence as a part of precision dairy farming to enable sustainable dairy farming	[143]
A124	Comparison of artificial neural networks and multiple linear regression for prediction of dairy cow locomotion score	[144]
A125	Can the use of digital technology improve cow milk productivity in large dairy herds? Evidence from China’s Shandong Province	[145]
A126	The Early Prediction of Common Disorders in Dairy Cows Monitored by Automatic Systems with Machine Learning Algorithms	[146]
A127	Fusion of udder temperature and size features for the automatic detection of dairy cow mastitis using deep learning	[147]
A128	Automatic Detection Method of Dairy Cow Feeding Behavior Based on YOLO Improved Model and Edge Computing	[148]
A129	Livestock Identification Using Deep Learning for Traceability	[149]
A130	Cattle face recognition based on a Two-Branch convolutional neural network	[150]
A131	YOLO-BYTE: An efficient multi-object tracking algorithm for automatic monitoring of dairy cows	[151]
A132	Early lameness detection in dairy cattle based on wearable gait analysis using semi-supervised LSTM-Autoencoder	[152]
A133	Dairy cow lameness detection using a back curvature feature	[153]
A134	Effect of body condition change and health status during early lactation on performance and survival of Holstein cows	[154]
A135	Cow identification in free-stall barns based on an improved Mask R-CNN and an SVM	[155]
A136	ResNet-based dairy daily behavior recognition	[156]
A137	Artificial Intelligence and Sensor Technologies in Dairy Livestock Export: Charting a Digital Transformation	[157]
A138	A Gradient Boosting model to predict the milk production	[158]
A139	Diagnosis of dairy cow diseases by knowledge-driven deep learning based on the text reports of illness state	[159]
A140	Using dorsal surface for individual identification of dairy calves through 3D deep learning algorithms	[160]
A141	Counterfactual Explanations for Prediction and Diagnosis in XAI	[161]
A142	A deep learning algorithm predicts milk yield and production stage of dairy cows utilizing ultrasound echotexture analysis of the mammary gland	[162]
A143	Data considerations for developing deep learning models for dairy applications: A simulation study on mastitis detection	[163]
A144	A Novel Framework to Perform Efficient Analysis of Animal Sciences Using Big Data	[164]
A145	Using Empirical Modal Decomposition to Improve the Daily Milk Yield Prediction of Cows	[165]
A146	Precision livestock agriculture and productive efficiency: The case of milk recording in Ireland	[166]
A147	Deep learning image recognition of cow behavior and an open data set acquired near an automatic milking robot	[167]
A148	Addressing Data Bottlenecks in the Dairy Farm Industry	[168]
A149	Data-Driven Surveillance: Effective Collection, Integration, and Interpretation of Data to Support Decision Making	[169]
A150	Growth, milk production, reproductive performance, and stayability of dairy heifers born from 2-year-old or mixed-age dams	[170]
A151	Lameness Detection in Cows Using Hierarchical Deep Learning and Synchrosqueezed Wavelet Transform	[171]
A152	Prediction of Polish Holstein economical index and calving interval using machine learning	[172]