Perbandingan Deteksi Objek Kemeja Putih dan Hitam menggunakan ANN dan CNN
Indonesia
DOI:
https://doi.org/10.30989/teknomatika.v17i2.1552Keywords:
Deteksi Objek, ANN, CNN, Kemeja, AnalisisAbstract
This study discusses the comparison of object detection of white shirts and black shirts using the Artificial Neural Network and Convolutional Neural Network methods. The purpose of this study is to analyze the performance of the two algorithms in recognizing color differences in objects and characteristics of shirts. The dataset used is a dataset of white and black shirts from various angles. In this study, it is known that the CNN method is superior in detecting black and white shirts with an accuracy of 41% compared to ANN, which reaches an accuracy of 29%.
References
[1] A. B. Amjoud and M. Amrouch, “Object Detection Using Deep Learning, CNNs and Vision Transformers: A Review,” IEEE Access, vol. 11, no. March, pp. 35479–35516, 2023, doi: 10.1109/ACCESS.2023.3266093.
[2] A. Wang et al., “YOLOv10 : Real-Time End-to-End Object Detection,” in Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 2024, pp. 1–28.
[3] M. P. Low, T. H. Cham, Y. S. Chang, and X. J. Lim, “Advancing on weighted PLS-SEM in examining the trust-based recommendation system in pioneering product promotion effectiveness,” Qual. Quant., vol. 57, no. s4, pp. 607–636, 2023, doi: 10.1007/s11135-021-01147-1.
[4] L. Marlina, S. Wahyuni, and I. Sulistianingsih, “International Journal of Computer Sciences and Mathematics Engineering The Information System for Promotion of Products for Micro, Small, and Medium Enterprises in Hinai Village is Website-Based With a Membership Method,” Int. J. Comput. Sci. Math. Eng., vol. 2, no. 2, 2023.
[5] A. Infante and R. Mardikaningsih, “The Potential of Social Media as a Means of Online Business Promotion,” J. Soc. Sci. Stud., vol. 2, no. 2, pp. 45–49, 2022, doi: 10.56348/jos3.v2i2.26.
[6] A. Shah et al., “A comprehensive study on skin cancer detection using artificial neural network (ANN) and convolutional neural network (CNN),” Clin. eHealth, vol. 6, pp. 76–84, 2023, doi: 10.1016/j.ceh.2023.08.002.
[7] T. A. Dompeipen and S. R. U. . Sompie, “Penerapan computer vision untuk pendeteksian dan penghitung jumlah manusia,” J. Tek. Inform., vol. 15, no. 4, pp. 1–12, 2020.
[8] M. M. A. Wona et al., “Klasifikasi Batik Indonesia Menggunakan Convolutional Neural Network (CNN),” J. Rekayasa Teknol. Inf., vol. 7, no. 2, p. 172, 2023, doi: 10.30872/jurti.v7i2.13694.
[9] Raden Roro Ayuni Purbo Okta Briliani and Irma Palupi, “Klasifikasi Penyakit Kulit menggunakan Image Processing dan Artificial Neural Network (ANN),” e-Proceeding Eng., vol. 9, no. 3, p. 1902, 2022.
[10] R. Hesananda, D. Natasya, and N. Wiliani, “Cloth Bag Object Detection Using the Yolo Algorithm (You Only See Once) V5,” J. Pilar Nusa Mandiri, vol. 18, no. 2, pp. 217–222, 2023, doi: 10.33480/pilar.v18i2.3019.
