SI1831490046

Dari widuri
(Dialihkan dari SK1831490046)
Lompat ke: navigasi, cari


IMPLEMENTASI DEEP LEARNING PADA PROTOTIPE PENGHITUNG

ANAK AYAM MEMANFAATKAN RASPBERRY PI 4


SKRIPSI



Disusun Oleh :

NIM : 1831490046
NAMA : MUHAMMAD SUZAKI ZAHRAN


FAKULTAS SAINS DAN TEKNOLOGI

PROGRAM STUDI SISTEM KOMPUTER

KONSENTRASI COMPUTER SYSTEM

UNIVERSITAS RAHARJA

TANGERANG

2022/2023


ABSTRAKSI

Konsumsi daging ayam Indonesia meningkat meski turun 7,89% pada tahun 2020 (BPS Indonesia). Konsumsi daging ayam Indonesia lebih rendah dari konsumsi global. Badan Pusat Statistik (BPS) memperkirakan produksi ayam pedaging pada 2021 mencapai 3,43 juta ton, naik 6,43 persen dari 3,22 juta pada 2020. Ekspansi ini mendorong permintaan daging ayam di Indonesia sehingga mendorong ekspansi peternakan ayam lebih lanjut. Setidaknya ada 12 jenis ayam broiler yang populer di Indonesia. Benih yang baik membantu perkembangan ayam broiler. Menghitung jumlah benih yang optimal juga penting. Produsen ayam sering mengimpor lebih dari 1.000 anak ayam. Kotak berisi 100 ayam pedaging umum digunakan. Jumlah anak ayam per kotak diperkirakan terlalu tinggi dan kematian tidak dapat diprediksi. Jumlah anak ayam yang salah dapat menyebabkan masalah kesehatan, biaya operasional yang lebih tinggi, dan kerugian karena tingkat kematian yang tinggi. Dengan demikian, penelitian ini mengembangkan penghitung bibit anak ayam berbasis kamera. Peternak dapat menggunakan alat penelitian ini untuk menghitung anak ayam yang didatangkan dengan cepat dan akurat dengan mengarahkan kamera ke arah bibit anak ayan dan menerima jumlah anak ayam yang dihitung dan jumlah totalnya.

Kata Kunci: Ayam Broiler, Bibit Ayam, Peternakan, Konsumsi Daging Ayam.

ABSTRACT

Indonesian chicken meat consumption has increased despite a 7.89% drop by 2020 (BPS Indonesia). Indonesian chicken meat consumption is lower than global consumption. The Badan Pusat Statistik (BPS) predicted 3.43 million tons of broiler production in 2021, up 6.43 percent from 3.22 million in 2020. This expansion boosted Indonesians' demand for chicken meat, forcing further chicken farm expansion. At least 12 varieties of broiler chickens are popular in Indonesia. Good seeds help broiler chicks develop. Calculating optimal seed quantities is also crucial. Chicken producers often import over 1,000 chicks. Boxes of 100 broiler chicks are common. The number of chicks per box is expected to be too high and mortality unpredictable. The wrong number of chicks can cause health issues, higher operational costs, and losses due to high mortality rates. Thus, our study developed a camera-based chick counter. Farmers can use this research instrument to quickly and accurately count imported chicks by aiming the camera at them and receiving the number of chicks counted and the total number.

Keywords: Broiler Chicken, Chicks, Farm, Chicken Meat Demand.


DAFTAR PUSTAKA

  1. 27+ Most Popular Computer Vision Applications in 2022. (n.d.). Retrieved May 15, 2022, from https://www.v7labs.com/blog/computer-vision-applications
  2. 27+ Most Popular Computer Vision Applications in 2022. (n.d.). Retrieved May 15, 2022, from https://www.v7labs.com/blog/computer-vision-applications
  3. Aasinjery. (2020). Pengantar Teknologi Sistem Informasi. Asinjery. About - OpenCV. (n.d.). Retrieved May 15, 2022, from https://opencv.org/about/
  4. Achmad Fiqhi Ibadillah., S. T. M. S. R. A. S. T. M. T. (2021). Mikrokontroler dan Aplikasinya. Media Nusa Creative (MNC Publishing).
  5. Ahram, T., & Karwowski, W. (2022). Human Factors in Robots, Drones and Unmanned Systems - Google Books. AHFE INTERNATIONAL.
  6. https://www.google.co.id/books/edition/Human_Factors_in_Robots_Drones_and_Unman/BN2VEAAAQBAJ?hl=en&gbpv=0
  7. Amaratunga, T. (2020). Deep Learning on Windows: Building Deep Learning Computer Vision Systems on Microsoft Windows. Apress.
  8. Ansari, S. (2020). Building Computer Vision Applications Using Artificial Neural Networks: With Step-by-Step Examples in OpenCV and TensorFlow with Python. Apress.
  9. Balon, B., & Simic, M. (2019). Using Raspberry Pi Computers in Education. 671–676. https://doi.org/10.23919/MIPRO.2019.8756967
  10. Baltzer, W., Hradilak, T., Pfennigschmidt, L., Prestin, L. M., Spranger, M.,
  11. Stadlinger, S., Wendt, L., Lincke, J., Rein, P., Church, L., Hirschfeld, R. 1969-, Hasso-Plattner-Institut für Digital Engineering, & Universitätsverlag Potsdam. (2021). An individual-centered approach to visualize people’s opinions and demographic information. Technische Berichte Des Hasso-Plattner-Instituts Für Digital Engineering an Der Universität Potsdam.
  12. https://books.google.com/books/about/An_individual_centered_approach_to_visua.html?id=eNlXEAAAQBAJ
  13. Bepery, C., Baral, S., Khashkel, A., & Hossain, F. (n.d.). ADVANCED HOME AUTOMATION SYSTEM USING RASPBERRY-PI AND ARDUINO.
  14. Bora, P., Kanakaraja, P., Chiranjeevi, B., Jyothi Sri Sai, M., & Jeswanth, A. (2021). Smart real time health monitoring system using Arduino and Raspberry Pi. Materials Today: Proceedings, 46, 3855–3859. https://doi.org/10.1016/J.MATPR.2021.02.290
  15. Chaudhari, K. G. (2019). Windmill Monitoring System Using Internet of Things with Raspberry Pi. SSRN Electronic Journal. https://doi.org/10.2139/SSRN.3729041
  16. Chen, C., Hanson, M., Chaturvedi, R., Mattke, S., Hillestad, R., & Liu, H. H. (2018). Economic benefits of microprocessor controlled prosthetic knees: A modeling study. Journal of NeuroEngineering and Rehabilitation, 15(1), 1–11. https://doi.org/10.1186/S12984-018-0405-8/FIGURES/4
  17. Cholisoh, N., Junaidi, J., & Safitri Sari, I. (2021). Rancangan Sistem Penginputan Judul Online KKP, TA/SKRIPSI Berbasis Laravel Pada Universitas Raharja. Technomedia Journal, 5(2 Februari), 248–258. https://doi.org/10.33050/TMJ.V5I2.1430
  18. Chowdhary, C. L., Alazab, M., Chaudhary, A., Hakak, S., & Gadekallu, T. R. (2021). Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches: Fundamentals, Technologies and Applications. Institution of Engineering & Technology.
  19. Danish, M., Verma, R., Brazauskas, J., Lewis, I., & Mortier, R. (2022). DeepDish on a diet: Low-latency, energy-efficient object-detection and tracking at the edge. EdgeSys 2022 - Proceedings of the 5th International Workshop on Edge Systems, Analytics and Networking, Part of EuroSys 2022, 43–48. https://doi.org/10.1145/3517206.3526273
  20. Dasril Aldo, S. K. M. K., Afriosa Syawitri, S. P. M. K., Alwendi, S. K. M. K., Darmansah, S. K. M. K., & Khairunnisa Samosir, S. K. M. K. (2021). DATA MINING. Insan Cendekia Mandiri. Data analysis in research: Why data, types of data, data analysis in qualitative and quantitative research | QuestionPro. (n.d.). Retrieved May 12, 2022, from https://www.questionpro.com/blog/data-analysis-in-research/
  21. Dey, S. (2021). Image Processing Masterclass with Python: 50+ Solutions and Techniques Solving Complex Digital Image Processing Challenges Using Numpy, Scipy, Pytorch and Keras (English Edition). BPB PUBN.
  22. Dr. Nurmah Semil, M. S. (2018). Pelayanan Prima Instansi Pemerintah: Kajian Kritis pada Sistem Pelayanan Publik di Indonesia. Kencana.
  23. Dr. Sri Wahyuni Hasibuan, M. P., Dr. Abdurrahman Misno, M. E. I., Ansri Jayanti, S. S. M. S., Sholahuddin, M., Ujang Syahrul Mubarrok, S. S. S. E. M. S. M. M., Dr. Abdul Wahab, S. S. M. S., Dr. Tasrim, S. E. M. S., Saryanto, S. P. T. M. P., Siswadi Sululing, S. E. M. A. A. C. A. A. C. P. A., & Baso Iping, S. E. M. H. (2021). Metodologi Penelitian Bidang Muamalah, Ekonomi Dan Bisnis. Media Sains Indonesia. Dumka, A., Ashok, A., Verma, P., & Verma, P. (2020). Advanced Digital Image Processing and Its Applications in Big Data. CRC Press.
  24. Ersoz, A., Phu, H., Kim, I., & Han, M. (2019). A Wireless Neurostimulator System with an Embedded ARMTM Microprocessor. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 5200–5203. https://doi.org/10.1109/EMBC.2019.8856311
  25. Ghael, H. D., Solanki, L., & Sahu, G. (2021). A Review Paper on Raspberry Pi and its Applications A Review Paper on Raspberry Pi and its Applications. January 2020, 10–13. https://doi.org/10.35629/5252-0212225227
  26. Ghaffar, A. I., Ibrahim, M. I., Aiman, M., Ahmad, A., & Ismail, M. F. (2022). Raspberry Pi Basic Tutorial using Android Application for Beginner User. 3(1), 510–516.
  27. Gnanaprakash, B., Meitei, M. A., Singh, A. S., Vamshi Krishna, O. M., & Kumar, V. S. (2018). RFID Security Access Control System using 8051 Microprocessor.
  28. Gollapudi, S. (2019). Learn Computer Vision Using OpenCV: With Deep Learning CNNs and RNNs. Apress.
  29. Hemanth, D. J. (2019). Artificial Intelligence Techniques for Satellite Image Analysis. Springer International Publishing.
  30. Howse, J., & Minichino, J. (2020). Learning OpenCV 4 Computer Vision with Python 3: Get to grips with tools, techniques, and algorithms for computer vision and machine learning, 3rd Edition. Packt Publishing.
  31. Ikeuchi, K. (2021). Computer Vision: A Reference Guide. Springer International Publishing.
  32. INDIAN JOURNAL OF SCIENCE AND TECHNOLOGY. (2020). https://doi.org/10.17485/IJST/v13i27.311
  33. Introduction to AI in Image Processing: Yuk Kenali Teknologi Paling Canggih Saat Ini! | BINUS UNIVERSITY. (n.d.). Retrieved May 15, 2022, from https://binus.ac.id/2021/04/introduction-to-ai-in-image-processing-yuk-kenali-teknologi-paling-canggih-saat-ini/
  34. Introduction to PyTorch | The Deep Learning with PyTorch Workshop. (n.d.). Retrieved December 17, 2022, from https://subscription.packtpub.com/book/data/9781838989217/1/ch01lvl1sec04/introduction-to-pytorch
  35. Jiang, K., Xie, T., Yan, R., Wen, X., Li, D., Jiang, H., Jiang, N., Feng, L., Duan, X., & Wang, J. (2022). An Attention Mechanism-Improved YOLOv7 Object Detection Algorithm for Hemp Duck Count Estimation. Agriculture 2022, Vol. 12, Page 1659, 12(10), 1659. https://doi.org/10.3390/AGRICULTURE12101659
  36. Kaplan, A. (2022). Artificial Intelligence, Business and Civilization: Our Fate Made in Machines. Taylor & Francis.
  37. Karakteristik Data untuk Informasi yang Berkualitas – School of Information Systems. (n.d.). Retrieved May 12, 2022, from https://sis.binus.ac.id/2019/04/05/karakteristik-data-untuk-informasi-yang-berkualitas/
  38. Ketut, I., Wirayasa, A., Djajadi, A., Santoso, A., & Indrajit, E. (2021). Comparison Non-Parametric Machine Learning Algorithms for Prediction of Employee Talent. IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 15(4), 403–414. https://doi.org/10.22146/ijccs.69366
  39. Khan, F. H., Pasha, M. A., & Masud, S. (2021). Advancements in microprocessor architecture for ubiquitous ai—an overview on history, evolution, and upcoming challenges in ai implementation. Micromachines, 12(6), 1–22. https://doi.org/10.3390/mi12060665
  40. Khan, S. A., Ahmad, I., Shufian, A., & Ahmed, M. S. (2019). A smart intruder alert system based on microprocessor and motion detection. 1st International Conference on Robotics, Electrical and Signal Processing Techniques, ICREST 2019, 2019-January, 335–339. https://doi.org/10.1109/ICREST.2019.8644109
  41. Khosrow-Pour, M. (2020). Encyclopedia of organizational knowledge, administration, and technology. Encyclopedia of Organizational Knowledge, Administration, and Technology, 1–2839. https://doi.org/10.4018/978-1-7998-3473-1
  42. Koirala, A., Jha, M., Bodapati, S., Mishra, A., Chetty, G., Sahu, P. K., Mohanty, S., Padhan, T. K., Mattoo, J., & Hukkoo, A. (2022). Deep Learning for Real-Time Malaria Parasite Detection and Counting Using YOLO-mp. IEEE Access, 10, 102157–102172. https://doi.org/10.1109/ACCESS.2022.3208270
  43. Kothari, G., & Verma, B. L. (2022). AI-Implanted E-Learning 4.0: A New Paradigm in Higher Education. Impact of Artificial Intelligence on Organizational Transformation, 305–325. https://doi.org/10.1002/9781119710301.CH18
  44. Lakshmanan, V., Görner, M., & Gillard, R. (2021). Practical Machine Learning for Computer Vision. O’Reilly Media.
  45. Lestari, K. C., & Amri, A. M. (2020). Sistem Informasi Akuntansi (beserta contoh penerapan aplikasi SIA sederhana dalam UMKM). Deepublish. Liou, F. W. (2022). Rapid prototyping and engineering applications : a toolbox for prototype development. Researchgate.
  46. Made, G., Desnanjaya, N., Nyoman, I., & Arsana, A. (2021). Home security monitoring system with IoT-based Raspberry Pi WIRELESS SENSOR NETWORK View project Automatic Balinese KULKUL View project I Gusti Made Ngurah Desnanjaya STMIK STIKOM Indonesia Home security monitoring system with IoT-based Raspberry Pi. Indonesian Journal of Electrical Engineering and Computer Science, 22(3), 1295–1302. https://doi.org/10.11591/ijeecs.v22.i3.pp1295-1302
  47. Manganiello, F. (n.d.). Computer vision with maker tech : detecting people with a Raspberry Pi, a thermal camera, and machine learning.
  48. Manojkumar, P., Suresh, M., Ayub Ahmed, A. Al, Panchal, H., Rajan, C. A.,
  49. Dheepanchakkravarthy, A., Geetha, A., Gunapriya, B., Mann, S., & Sadasivuni, K. K. (2021). A novel home automation distributed server management system using Internet of Things. Https://Doi.Org/10.1080/01430750.2021.1953590. https://doi.org/10.1080/01430750.2021.1953590
  50. Márquez, G., Gomes, H., Redinha, N., Lavado, N., & Mendes, M. (2022). Counting People and Bicycles in Real Time Using YOLO on Jetson Nano. Energies 2022, Vol. 15, Page 8816, 15(23), 8816. https://doi.org/10.3390/EN15238816
  51. Maulani, G., Komara, H., & Meiliana, S. (2020). Rancang Bangun Sistem Informasi Monitoring Dashboard Traffic Work Order Berbasis Web. Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics, 6(2), 137–146. https://doi.org/10.33050/CERITA.V6I2.1127
  52. Mer, A., & Virdi, A. S. (2022). Artificial Intelligence Disruption on the Brink of Revolutionizing HR and Marketing Functions. Impact of Artificial Intelligence on Organizational Transformation, 1–19. https://doi.org/10.1002/9781119710301.CH1
  53. Mythili, R., Reddy, P. N., Keerthivasan, B., & Sooriya, V. (2021). Encrypted NAS using Raspberry Pi 4. 2021 5th International Conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques, ICEECCOT 2021 - Proceedings, 675–680. https://doi.org/10.1109/ICEECCOT52851.2021.9707921
  54. Nasron, S. T. M. T. (2021). Sistem Mikroprosesor. Penerbit Andi.
  55. Ningsih, R., Suryani, A. I., Sinlae, A. A. J., Harmayani, H., Parewe, A. M. A. K., Halid, A., Markani, M., Jamaludin, J., Siagian, Y., & Puteri, A. N. (2022). Perancangan Basis Data. Yayasan Kita Menulis.
  56. Nuryono Satya Widodo, S. T. M. E., & Asyhari, B. (2021). Buku Ajar Sistem Berbasis Mikroprosesor. UAD PRESS.
  57. Olmoguez, I. L. G., Catindig, M. A. C., Amongos, M. F. Lou, & Lazan, F. G. (2019). Developing a dengue forecasting model: A case study in Iligan City. International Journal of Advanced Computer Science and Applications, 10(9), 281–286. https://doi.org/10.14569/ijacsa.2019.0100936
  58. Oltean, S. E. (2019). Mobile Robot Platform with Arduino Uno and Raspberry Pi for Autonomous Navigation. Procedia Manufacturing, 32, 572–577. https://doi.org/10.1016/J.PROMFG.2019.02.254
  59. OpenCV - Overview - GeeksforGeeks. (n.d.). Retrieved May 15, 2022, from https://www.geeksforgeeks.org/opencv-overview/
  60. OpenVINOTM Documentation — OpenVINOTM documentation — Version(latest). (n.d.). Retrieved May 15, 2022, from https://docs.openvino.ai/latest/index.html
  61. Pal, S. K., Pramanik, A., Maiti, J., & Mitra, P. (2021). Deep learning in multi-object detection and tracking: state of the art. Applied Intelligence 2021 51:9, 51(9), 6400–6429. https://doi.org/10.1007/S10489-021-02293-7
  62. Park, H., Ou, S., & Lee, J. (2021). Implementation of Multi-Object Recognition System for the Blind. INTELLIGENT AUTOMATION AND SOFT COMPUTING, 29(1), 247–258. https://doi.org/10.32604/IASC.2021.015274
  63. Program, M., Informatika, S. T., Dinamika Bangsa, S., Jendral, J. J., & Thehok -Jambi, S. (2018). Perancangan Prototype Aplikasi Pengelolaan Inventaris Barang. Jurnal Ilmiah Media Sisfo, 12(2), 1099–1110. http://ejournal.stikom-db.ac.id/index.php/mediasisfo/article/view/407
  64. Pros and Cons of Raspberry Pi: Detailed Guide in 2020. (n.d.). Retrieved May 15, 2022, from https://robu.in/5-pros-and-5-cons-of-raspberry-pi/
  65. PyTorch vs. TensorFlow: 2022 Deep Learning Comparison | Built In. (n.d.). Retrieved December 17, 2022, from https://builtin.com/data-science/pytorch-vs-tensorflow
  66. Quan, H., & Ablameyko, S. (2022). MULTI-OBJECT TRACKING BY USING STRONG SORT TRACKER AND YOLOV7 NETWORK.
  67. Rahayu, S., Alfeno, S., Wahyono, K. N., Amik, D., Informatika, R., Stmik Raharja, D., Stmik, M., & Informatika, R. T. (2019). RANCANG BANGUN APLIKASI SISTEM PENGOLAHAN DATA PEMBUATAN AKTA TANAH PADA KANTOR DESA CANGKUDU TANGERANG. 5(1).
  68. Rahayu, S., Rachmanda, P., & Putri, A. L. (2022). Creative Education of Research in Information Technology and Artificial informatics Perancangan Sistem Informasi Pelayanan Pembuatan Surat Menyurat Berbasis Web Pada Kantor Desa Saga. CERITA Journal.
  69. Ramani, K., Suneetha, I., Pushpalatha, N., Harish, P., & Yugandhar, P. (2022). Efficient Multi-Object Identification and Guiding System for Visually Impaired. Journal of Pharmaceutical Negative Results, 13(4), 1019–1023. https://doi.org/10.47750/pnr.2022.13.04.139
  70. Raspberry Pi 4 Model B specifications – Raspberry Pi. (n.d.). Retrieved May 15, 2022, from https://www.raspberrypi.com/products/raspberry-pi-4-model-b/specifications/
  71. Raspberry Pi 4 Reviews, Pros and Cons | TechSpot. (n.d.). Retrieved May 15, 2022, from https://www.techspot.com/products/desktop-pcs/raspberry-pi-4.205636/
  72. Roihan, A., Hasanudin, M., Sunandar, E., Nggadas, D. E. P., & Anggraini, N. D. (2020). MONOGRAF: Purwarupa Bird Repellent Device Sebagai Optimalisasi Panen Dalam Bidang Pertanian Berbasis Internet of Things. LAKEISHA.
  73. Romindo, R., Muttaqin, M., Rasinus, R., Israwan, L. M. F., Yuswardi, Y., Karim, A., Sari, A. N., Putri, E. E., Samosir, K., & Simarmata, J. (2021). Sistem Informasi. Yayasan Kita Menulis.
  74. Romli, I., Romli, I., Hidayat, M. A., & Naya, C. (2021). Monitoring and assembly of internet of things-based solar power plants. Teknika: Jurnal Sains Dan Teknologi, 17(2), 228–234. https://doi.org/10.36055/tjst.v17i2.12358
  75. Santi, I. H. (2020). ANALISA PERANCANGAN SISTEM. Penerbit NEM.
  76. Santoso, S., & Novita, W. (2019). APLIKASI SISTEM INFORMASI PEMANTAUAN INVENTORY STOCK OPNAME BERBASIS WEB PADA PT MAKMUR BERKAT SOLUSI LOGISTIC. 5(2).
  77. Sathyanarayanan, S., & Chitnis, S. (2022). A Survey of Machine Learning in Healthcare. Artificial Intelligence Applications for Health Care, 1–22. https://doi.org/10.1201/9781003241409-1
  78. Schell, B. (2019). Computing with the Raspberry Pi: Command Line and GUI Linux. Apress.
  79. Sinduningrum, E. (2020). Teori Organisasi Arsitektur Komputer & Praktik Assembler Untuk Pemula. Deepublish.
  80. Singla, V. K., Aggarwal, V., Priyanka, & Gupta, S. (2021). Artificial Intelligence and Nanotechnology : A Super Convergence. Artificial Intelligence, 1–8. https://doi.org/10.1201/9781003095910-1
  81. Socio-technical standards for a resource-based community. (n.d.). Retrieved January 2, 2023, from https://auravana.org/standards/
  82. Stolojescu-Crisan, C., Crisan, C., & Butunoi, B. P. (2021). An IoT-Based Smart Home Automation System. Sensors 2021, Vol. 21, Page 3784, 21(11), 3784. https://doi.org/10.3390/S21113784
  83. Subakti, H., Kraugusteeliana, Purabaya, R. H., Muslih, M., Sasongko, D., Yahya, Syamsiyah, N., Herianto, Krisnanik, E., Syah, A. Z., & Syofian, S. (2022). Interaksi Manusia dan Komputer - - Google Books. Media Sains Indonesia Dan Penulis. https://books.google.co.id/books?id=JwdlEAAAQBAJ&pg=PA67&lpg=PA67&dq=%22prototype+adalah+representasi+desain+yang+dalam+beberapa+hal+merupakan+beberapa+bagian+atau+fitur+dari+produk+yang+lengkap.%E2%80%9D&source=bl&ots=W8Oy8LmM6i&sig=ACfU3U12EQDdtVP-z8FltL743h_VC2YDRA&hl=en&sa=X&ved=2ahUKEwiN9cr5l6n8AhV6SmwGHX9bBfUQ6AF6BAgJEAM#v=onepage&q=%22prototype%20adalah%20representasi%20desain%20yang%20dalam%20beberapa%20hal%20merupakan%20beberapa%20bagian%20atau%20fitur%20dari%20produk%20yang%20lengkap.%E2%80%9D&f=false
  84. Suyanto, Y., & Press, U. G. M. (2018). Pemograman Terstruktur dengan Delphi. UGM PRESS.
  85. Suyuti, R. N. M. A. (2018). Perancangan Mesin-Mesin Industri. Deepublish.
  86. Szeliski, R. (2021). Computer Vision : Algorithms and Applications 2nd Edition. Springer, 1196.
  87. Takano, S. (2021). Thinking Machines: Machine Learning and Its Hardware Implementation. Elsevier Science.
  88. Togelius, J. (2019). Playing Smart: On Games, Intelligence, and Artificial Intelligence. MIT Press.
  89. Verdhan, V. (2021). Computer Vision Using Deep Learning: Neural Network Architectures with Python and Keras. Apress.
  90. Wang, C.-Y., Bochkovskiy, A., & Liao, H.-Y. M. (2022). YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors. https://doi.org/10.48550/arxiv.2207.02696
  91. What is a Flowchart and its Types? - GeeksforGeeks. (n.d.). Retrieved May 15, 2022, from https://www.geeksforgeeks.org/what-is-a-flowchart-and-its-types/
  92. What is a Flowchart? Symbols, Types, and How To Read it • Asana. (n.d.). Retrieved May 15, 2022, from https://asana.com/resources/what-is-a-flowchart
  93. What is a Microprocessor and How Does it Work? (n.d.). Retrieved May 15, 2022, from https://www.brainspire.com/blog/what-is-a-microprocessor-and-how-does-it-work
  94. What is Data Analysis? Methods, Techniques & Tools. (n.d.). Retrieved May 12, 2022, from https://hackr.io/blog/what-is-data-analysis-methods-techniques-tools
  95. What Is Data Analysis? Methods, Techniques, Types & How-To. (n.d.-a). Retrieved May 12, 2022, from https://www.datapine.com/blog/data-analysis-methods-and-techniques/
  96. What Is Data Analysis? Methods, Techniques, Types & How-To. (n.d.-b). Retrieved May 12, 2022, from https://www.datapine.com/blog/data-analysis-methods-and-techniques/
  97. What Is Data Processing: Definition, Cycle, Types & Methods [Updated] | Simplilearn. (n.d.). Retrieved May 12, 2022, from https://www.simplilearn.com/what-is-data-processing-article
  98. What Is Image Processing: Overview, Applications, Benefits, and Who Should Learn It [2022 Edition]. (n.d.). Retrieved May 15, 2022, from https://www.simplilearn.com/image-processing-article
  99. What is Microprocessor? Types of Microprocessors & Applications. (n.d.). Retrieved May 15, 2022, from https://www.electricaltechnology.org/2020/05/types-of-microprocessors.html
  100. What is OpenVINO? - The Ultimate Overview (Updated) - viso.ai. (n.d.). Retrieved May 15, 2022, from https://viso.ai/computer-vision/intel-openvino-toolkit-overview/
  101. What is PyTorch, and How Does It Work? | Simplilearn. (n.d.). Retrieved December 17, 2022, from https://www.simplilearn.com/what-is-pytorch-article
  102. Wijoyo, H. (2021). SISTEM INFORMASI MANAJEMEN. Insan Cendekia Mandiri.
  103. Yadav, V. K., Yadav, P., & Sharma, S. (n.d.). An Efficient Yolov7 and Deep Sort are Used in a Deep Learning Model for Tracking Vehicle and Detection. Retrieved December 17, 2022, from http://xisdxjxsu.asia
  104. Yang, F., Zhang, X., & Liu, B. (2022). Video object tracking based on YOLOv7 and DeepSORT. https://doi.org/10.48550/arxiv.2207.12202
  105. Zaidi, S. S. A., Ansari, M. S., Aslam, A., Kanwal, N., Asghar, M., & Lee, B. (2022). A survey of modern deep learning based object detection models. Digital Signal Processing, 126, 103514. https://doi.org/10.1016/J.DSP.2022.103514
  106. Zhang, Y., Sun, P., Jiang, Y., Yu, D., Weng, F., Yuan, Z., Luo, P., Liu, W., & Wang, X. (2022). ByteTrack: Multi-object Tracking by Associating Every Detection Box. 1–21. https://doi.org/10.1007/978-3-031-20047-2_1/COVER

Contributors

Admin

Diperoleh dari "https://widuri.raharja.info/index.php?title=SI1831490046&oldid=397430"