The Academic Resources Recommender System (ARReS) includes collection of Theses and Dissertations available in the Camarines Sur Polytechnic Colleges Library.
Technological advancement in poultry farming has been an advantage in poultry production. Applying a traditional method of sorting the broiler chicks might result in low-quality poultry production due to some factors encountered. Whereas, this study developed a system prototype that applies image classification using image processing and fuzzy logic algorithm. This system prototype focused on image classification that classifies the physical parameters of broiler chicks from collected image datasets, such as position and eye parameters. The Convolutional Neural Network performs as a neural network model for training the datasets. Subsequently, the fuzzy logic undertook the identification and classification of the image based on analyzing the parameters of the broiler chick. Throughout the study, the Agile Model serves as the system methodology that applies the combination of both iterative and incremental processes. This study used descriptive-qualitative research to acquire data using the procedure of interviews and surveys with open-ended questions in particular respondents, specifically the poultry farmers and licensed agriculturists. Upon the accuracy rate of correct prediction, the result is 95% which occurs when the system prototype runs and processes the classification of images. The fuzzy logic and CNN, have undergone an evaluation which resulted in 98% for training and 100% for testing. From this basis, the model will only make minor errors on a tiny portion of the data, which is the optimal situation. As a result, the overall outcomes revealed that using image processing and fuzzy logic algorithms to develop a broiler chick's classifier is feasible in image classification.
Namirah L. Balindong; Arnold S. Sayat Jr.; Mat Andrew V. Tantiado; Rose Ann B. Sabilla; Mary Rose T. Lazaro
2022 Computer ScienceThe convolutional neural network is one of the most promising applications in computer vision. Deep learning-based classification has recently enabled the recognition of chickens from images. However, no research has been done on using the Convolutional Neural Network (CNN) Algorithm in image proces...
Janet B. Sasaluya; Caren F. Vega; Crystallene R. Lagatic; Louis Carlo SF. Fornoles
2022 Computer ScienceHarvesting the rice plant too early resulted in a higher percentage of unfilled or immature grains, lowering production and increasing grain breakage during milling. However, harvesting rice too late resulted in severe losses and breakage. This problem pushed the researchers to create a model that h...
Hamadie Seed D. Alswaidi; Anthony B. Amilano; Felix Jose I. Awa; Marian Mildred D. Bedural
2022 Computer ScienceCoconut diseases cause production problem. In connection with this, the study aimed to gather and collect datasets of healthy coconut leaves and with coconut diseases particularly Graphiola Leaf Spot, Stigmina Leaf Spot, and Whiteflies; create a CNN model for detecting the specified coconut diseases...
Rose Ann R. Navales; Judy Ann Soliman; Marlou B. Toledo; Filbert O. Tucio
2022 Computer ScienceThe research, “Rice Paddy Moisture Content Classification using Convolutional Neural Network,” was created to assist rice farmers and dealers in classifying rice paddy to determine moisture content. Also, the researcher used an experimental research design to perform research in an objective and con...