The Academic Resources Recommender System (ARReS) includes collection of Theses and Dissertations available in the Camarines Sur Polytechnic Colleges Library.
The 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 processing to identify chicken breeds. In this paper, CNN is proposed for the classification of the input chicken breed images. The goal of this research is to provide knowledge and understanding of different chicken breeds for everyone who will benefit in the future, and to help the poultry farm by developing an application using the CNN algorithm. This study used quantitative research and methods to develop the system. The dataset utilized for this study was composed of a minimum of 500 photos from 12 distinct categories, namely Jersey Giant, Shamo, Black Australorpe, Brahma, Rhode Island Red, Barred Plymouth Rock, Peruvian Black Knight, Rhode Island White, Decalb Brown, Hubbard Sasso, Blackstar, and Kabir. The photos were collected from the IRiganeo Organic Chicken RC'Farm in Iriga City and other secondary data available on the internet. Furthermore, the 6,493 images in the collected image dataset were divided into two groups: 80% for training and 20% for testing. Through the confusion matrix, the testing accuracy was achieved at 71.2% and the training accuracy at 99%. The overall performance was obtained using a different number of training and test images. The CNN provides better results when the dataset is large and includes high-quality resolution images. The developed prototype proposed method has positive effects.
Eva Eunice C. Moreno; Erica Rose R. Agullo; Carla Mae M. Posiquit; Sarah Jane B. De Lima
2022 Computer ScienceTechnological 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 cl...
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...
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...
Jonalyn L. Bugnot; Kim Clarice Garcia; Jude Romar B. Cerdeño; Maria Jessica T. Sayin
2022 Computer ScienceClassification of waste is one common problem in waste management, waste can bring a huge impact in everyday living causing pollution and some other infectious diseases. The traditional way of sorting waste manually takes much time and brings negative effect as it is already contaminated. Generally,...