Journal of Applied Computer Science and Technology最新文献

Perbandingan Metode Random Forest, Convolutional Neural Network, dan Support Vector Machine Untuk Klasifikasi Jenis Mangga 随机森林、卷积神经网络和支持向量机的使用方法

Journal of Applied Computer Science and Technology Pub Date : 2024-05-12 DOI: 10.52158/jacost.v5i1.742

Ricky Mardianto, Stefanie Quinevera, Siti Rochimah

{"title":"Perbandingan Metode Random Forest, Convolutional Neural Network, dan Support Vector Machine Untuk Klasifikasi Jenis Mangga","authors":"Ricky Mardianto, Stefanie Quinevera, Siti Rochimah","doi":"10.52158/jacost.v5i1.742","DOIUrl":"https://doi.org/10.52158/jacost.v5i1.742","url":null,"abstract":"Mango is a fruit known as the \"King of Fruit\" due to its rich flavor, vast variability, and high nutritional value. Classifying mangoes based on their external appearance is the initial step in the process of identifying and categorizing mango types conventionally. The classification process can be performed by examining external features such as fruit color, shape, and size. Classifying different types of mango fruits accurately can assist researchers in developing superior varieties and also aid farmers for cultivation purposes, sales, distribution, and selecting the right varieties for local growth and weather conditions. This research conducts the classification of mango types based on color from mango images using machine learning. The study compares three methods, namely Random Forest, Support Vector Machine (SVM), and Convolutional Neural Network (CNN), to determine the best method for classifying mango types based on their images. The dataset underwent preprocessing, where image sizes were standardized to 300 x 300 pixels, and color was changed to grayscale. The dataset was then divided into training and testing data with a ratio of 70:30. Subsequently, the dataset was processed using three methods, and their accuracy results were compared. The findings indicate that the Random Forest method yielded the highest accuracy compared to the other methods, with an accuracy rate of 96%. The accuracy of the SVM method was 95%, and the accuracy of the CNN method was 33%. From these results, it can be concluded that the Random Forest method is highly effective for classifying mango types based on their image compared to SVM and CNN methods. \u0000 ","PeriodicalId":493006,"journal":{"name":"Journal of Applied Computer Science and Technology","volume":"121 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140986416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Aktivitas Dinamis pada Appreciative Game “Warik the Adventurer” berbasis Finite State Machine 基于有限状态机的赞赏式游戏 "冒险家瓦里克 "中的 "动态 "问题

Journal of Applied Computer Science and Technology Pub Date : 2024-02-04 DOI: 10.52158/jacost.v5i1.716

Muhammad Rakha' Naufal, Hanny Haryanto, K. Hastuti, Nita Virena Nathania

{"title":"Aktivitas Dinamis pada Appreciative Game “Warik the Adventurer” berbasis Finite State Machine","authors":"Muhammad Rakha' Naufal, Hanny Haryanto, K. Hastuti, Nita Virena Nathania","doi":"10.52158/jacost.v5i1.716","DOIUrl":"https://doi.org/10.52158/jacost.v5i1.716","url":null,"abstract":"Serious games have become potential tools for education due to their advantage of giving a fun experience to the learner. Therefore, game experience is a fundamental element in serious game design. The game experience is mainly produced by the game activity, such as a quest or mission. However, in many serious games, the game activities do not have a clear design and concept, resulting in a poor playing experience which produce poor understanding of the material. Appreciative Game is a game that is based on Appreciative Learning concept. Appreciative Learning concepts could be used to design game activities. Appreciative Learning consists of four main stages. The stages are discovery, dream, design, and destiny. These four stages lay down the foundation of serious game activity. This study uses the Finite State Machine to produce intelligent agents in order to develop more dynamic game activity to enhance the game experience. We developed a 3D game called Warik the Adventurer as the testbed for this research. The game is about the cultural diversity in Indonesia. The game Experience Questionnaire (GEQ) is used to evaluate the player experience. The GEQ resulted in an acceptable score of 3 out of 5.","PeriodicalId":493006,"journal":{"name":"Journal of Applied Computer Science and Technology","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139867271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Chatbot Informasi Penerimaan Mahasiswa Baru Menggunakan Metode FastText dan LSTM 使用 FastText 和 LSTM 方法的新生入学信息聊天机器人

Journal of Applied Computer Science and Technology Pub Date : 2024-02-04 DOI: 10.52158/jacost.v5i1.648

Fahmi Yusron Fiddin, Agus Komarudin, Melina Melina

{"title":"Chatbot Informasi Penerimaan Mahasiswa Baru Menggunakan Metode FastText dan LSTM","authors":"Fahmi Yusron Fiddin, Agus Komarudin, Melina Melina","doi":"10.52158/jacost.v5i1.648","DOIUrl":"https://doi.org/10.52158/jacost.v5i1.648","url":null,"abstract":"New Student Admission (PMB) is an important stage in the continuity of education in an educational institution. The Faculty of Science and Informatics (FSI) at Jenderal Achmad Yani University (UNJANI) provides information services about PMB to prospective students and parents/guardians of prospective students but is still inefficient, so it is necessary to improve PMB information services by using Chatbots as a solution that is able to serve questions effectively and consistent. This study aims to develop a PMB information Chatbot system for FSI using the FastText and Long Short-Term Memory (LSTM) methods. Several methods have been used in Chatbot development research, such as Term Frequency–Inverse Document Frequency (TF-IDF), Bag of Words (BoW), and Convolutional Neural Networks (CNN). However, these studies still have certain limitations, such as the inability to grasp the meaning of words and difficulties in handling certain inputs. In this study, the text classification model uses the FastText method as the stage for representing words in vector form, then combined with several pre-processing methods (Tokenization & Casefolding) and LSTM for the classification stage. Then put it into the Chatbot component according to the architecture that was made. In testing, the Black Box Testing method is used to ensure the functionality of the Chatbot system. The test results show that the Chatbot system is able to understand the topic of questions asked by users properly. The interaction between users and Chatbots also runs smoothly, resulting in appropriate and informative responses. The results of this study are expected to be an effective and consistent solution for providing information about PMB to prospective students and parents/guardians of prospective students at FSI.","PeriodicalId":493006,"journal":{"name":"Journal of Applied Computer Science and Technology","volume":"19 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139866683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Chatbot Informasi Penerimaan Mahasiswa Baru Menggunakan Metode FastText dan LSTM 使用 FastText 和 LSTM 方法的新生入学信息聊天机器人

Journal of Applied Computer Science and Technology Pub Date : 2024-02-04 DOI: 10.52158/jacost.v5i1.648

Fahmi Yusron Fiddin, Agus Komarudin, Melina Melina

{"title":"Chatbot Informasi Penerimaan Mahasiswa Baru Menggunakan Metode FastText dan LSTM","authors":"Fahmi Yusron Fiddin, Agus Komarudin, Melina Melina","doi":"10.52158/jacost.v5i1.648","DOIUrl":"https://doi.org/10.52158/jacost.v5i1.648","url":null,"abstract":"New Student Admission (PMB) is an important stage in the continuity of education in an educational institution. The Faculty of Science and Informatics (FSI) at Jenderal Achmad Yani University (UNJANI) provides information services about PMB to prospective students and parents/guardians of prospective students but is still inefficient, so it is necessary to improve PMB information services by using Chatbots as a solution that is able to serve questions effectively and consistent. This study aims to develop a PMB information Chatbot system for FSI using the FastText and Long Short-Term Memory (LSTM) methods. Several methods have been used in Chatbot development research, such as Term Frequency–Inverse Document Frequency (TF-IDF), Bag of Words (BoW), and Convolutional Neural Networks (CNN). However, these studies still have certain limitations, such as the inability to grasp the meaning of words and difficulties in handling certain inputs. In this study, the text classification model uses the FastText method as the stage for representing words in vector form, then combined with several pre-processing methods (Tokenization & Casefolding) and LSTM for the classification stage. Then put it into the Chatbot component according to the architecture that was made. In testing, the Black Box Testing method is used to ensure the functionality of the Chatbot system. The test results show that the Chatbot system is able to understand the topic of questions asked by users properly. The interaction between users and Chatbots also runs smoothly, resulting in appropriate and informative responses. The results of this study are expected to be an effective and consistent solution for providing information about PMB to prospective students and parents/guardians of prospective students at FSI.","PeriodicalId":493006,"journal":{"name":"Journal of Applied Computer Science and Technology","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139806751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Aktivitas Dinamis pada Appreciative Game “Warik the Adventurer” berbasis Finite State Machine 基于有限状态机的赞赏式游戏 "冒险家瓦里克 "中的 "动态 "问题

Journal of Applied Computer Science and Technology Pub Date : 2024-02-04 DOI: 10.52158/jacost.v5i1.716

Muhammad Rakha' Naufal, Hanny Haryanto, K. Hastuti, Nita Virena Nathania

{"title":"Aktivitas Dinamis pada Appreciative Game “Warik the Adventurer” berbasis Finite State Machine","authors":"Muhammad Rakha' Naufal, Hanny Haryanto, K. Hastuti, Nita Virena Nathania","doi":"10.52158/jacost.v5i1.716","DOIUrl":"https://doi.org/10.52158/jacost.v5i1.716","url":null,"abstract":"Serious games have become potential tools for education due to their advantage of giving a fun experience to the learner. Therefore, game experience is a fundamental element in serious game design. The game experience is mainly produced by the game activity, such as a quest or mission. However, in many serious games, the game activities do not have a clear design and concept, resulting in a poor playing experience which produce poor understanding of the material. Appreciative Game is a game that is based on Appreciative Learning concept. Appreciative Learning concepts could be used to design game activities. Appreciative Learning consists of four main stages. The stages are discovery, dream, design, and destiny. These four stages lay down the foundation of serious game activity. This study uses the Finite State Machine to produce intelligent agents in order to develop more dynamic game activity to enhance the game experience. We developed a 3D game called Warik the Adventurer as the testbed for this research. The game is about the cultural diversity in Indonesia. The game Experience Questionnaire (GEQ) is used to evaluate the player experience. The GEQ resulted in an acceptable score of 3 out of 5.","PeriodicalId":493006,"journal":{"name":"Journal of Applied Computer Science and Technology","volume":"1999 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139807614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deteksi Helm Keselamatan Menggunakan Jetson Nano dan YOLOv7 使用 Jetson Nano 和 YOLOv7 检测安全头盔

Journal of Applied Computer Science and Technology Pub Date : 2024-02-03 DOI: 10.52158/jacost.v5i1.637

Hadi Supriyanto, Sarosa Castrena Abadi, Aliffa Shalsabilah

{"title":"Deteksi Helm Keselamatan Menggunakan Jetson Nano dan YOLOv7","authors":"Hadi Supriyanto, Sarosa Castrena Abadi, Aliffa Shalsabilah","doi":"10.52158/jacost.v5i1.637","DOIUrl":"https://doi.org/10.52158/jacost.v5i1.637","url":null,"abstract":"Increasing awareness of the importance of head personal protective equipment in industrial and construction environments has become a major concern in efforts to improve occupational safety. This research developed an early detection system for the use of computer vision-based head protective equipment using the YOLOv7 model and the Jetson Nano controller. The YOLOv7 algorithm was chosen for its ability for fast and accurate object detection. The YOLOv7 model was trained with a total dataset of 2799 images and iterations of 100 epochs to detect head personal protective equipment with a high degree of accuracy. The system captures imagery, activates a warning alarm, and sends a notification to Telegram when a violation occurs on an object that is not wearing a safety helmet. The test results using the confusion matrix method showed that the developed system was able to detect head personal protective equipment with an accuracy rate of 97.23%, which shows the system's ability to recognize personal protective equipment with very high accuracy. In addition, the system also showed a precision value of 98.71% indicating that all detections performed were correct, and a recall of 95.63% which describes the system's ability to recognize most of the head personal protective equipment available. The average FPS result using GPU with CUDA on Jetson Nano reached 5,723 FPS.","PeriodicalId":493006,"journal":{"name":"Journal of Applied Computer Science and Technology","volume":"54 5-6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139868402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Desktop Application for Traceability System on The Printed Circuit Board (PCB) Storage Process 印刷电路板 (PCB) 存储过程可追溯系统的桌面应用程序

Journal of Applied Computer Science and Technology Pub Date : 2024-02-03 DOI: 10.52158/jacost.v5i1.670

Alvin, Eko Rudiawan Jamzuri

{"title":"Desktop Application for Traceability System on The Printed Circuit Board (PCB) Storage Process","authors":"Alvin, Eko Rudiawan Jamzuri","doi":"10.52158/jacost.v5i1.670","DOIUrl":"https://doi.org/10.52158/jacost.v5i1.670","url":null,"abstract":"This paper discusses the development of desktop applications for traceability systems. The application was developed to facilitate data recording and tracking in an electronics manufacturing company's storage process of Printed Circuit Board (PCB) products. The application is developed using the Visual Basic language and Microsoft Excel databases. Additionally, the application is integrated with a barcode scanner to simplify the data entry process from PCBs and employee ID cards. Through the trial process conducted on the developed application, it has generally functioned in accordance with the development goals. Program control validation has been tested through several application access attempts from users registered as operators and administrators. The application has successfully recorded data from inbound and outbound processes, demonstrating storage and tracking functionality. Furthermore, the application has displayed the actual status data of the PCBs present in the warehouse. In terms of user satisfaction, seven users stated that this application was effective and efficient compared to the manual data recording process previously used by the company. This result was obtained from a questionnaire after the application was implemented in the company warehouse.","PeriodicalId":493006,"journal":{"name":"Journal of Applied Computer Science and Technology","volume":"48 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139868699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analisis Sentimen: Pengaruh Jam Kerja Terhadap Kesehatan Mental Generasi Z 情感分析：工作时间对 Z 世代心理健康的影响

Journal of Applied Computer Science and Technology Pub Date : 2024-02-03 DOI: 10.52158/jacost.v5i1.715

Muhammad Daffa Al Fahreza, Ardytha Luthfiarta, Muhammad Rafid, Michael Indrawan

{"title":"Analisis Sentimen: Pengaruh Jam Kerja Terhadap Kesehatan Mental Generasi Z","authors":"Muhammad Daffa Al Fahreza, Ardytha Luthfiarta, Muhammad Rafid, Michael Indrawan","doi":"10.52158/jacost.v5i1.715","DOIUrl":"https://doi.org/10.52158/jacost.v5i1.715","url":null,"abstract":"Mental health is a significant concern in society today, particularly for Generation Z, who are vulnerable to experiencing mental health problems that can disrupt daily productivity. The influence of working hours also contributes to the mental health of this generation. To assess public opinion on this issue, sentiment analysis is needed on social media, especially twitter. This research uses the Gaussian Naïve Bayes algorithm and Support Vector Machine with various stemming algorithms such as Nazief-Adriani, Arifin Setiono, and Sastrawi. The sentiment analysis method is used to assess positive, negative, and neutral sentiment in related tweets. The research results show that the Sastrawi stemming algorithm on the Gaussian Naïve Bayes model achieves 84% precision, 84% recall, and 84% f1-score, with 84% accuracy. Meanwhile, Support Vector Machine achieved 91% precision, 90% recall, 90% f1-score, and 91% accuracy. The Nazief-Adriani stemming algorithm on the Gaussian Naïve Bayes model has 80% precision, 80% recall, and 80% f1-score, with 80% accuracy. Meanwhile, on the Support Vector Machine, precision is 87%, recall is 85%, f1-score is 86%, and accuracy is 85%. Arifin Setiono's stemming algorithm on the Gaussian Naïve Bayes model achieved 81% precision, 81% recall, 81% f1-score, with 82% accuracy, while on Support Vector Machine, 88% precision, 86% recall, 86% f1-score, with 86% accuracy. Public opinion was recorded as 33% positive, 9% neutral, and 58% negative. This research aims to increase public awareness of the importance of mental health, especially regarding the influence of working hours, to create a healthy work environment for Generation Z and society in general, as well as improving the quality of mental health.","PeriodicalId":493006,"journal":{"name":"Journal of Applied Computer Science and Technology","volume":"36 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139867525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Desktop Application for Traceability System on The Printed Circuit Board (PCB) Storage Process 印刷电路板 (PCB) 存储过程可追溯系统的桌面应用程序

Journal of Applied Computer Science and Technology Pub Date : 2024-02-03 DOI: 10.52158/jacost.v5i1.670

Alvin, Eko Rudiawan Jamzuri

{"title":"Desktop Application for Traceability System on The Printed Circuit Board (PCB) Storage Process","authors":"Alvin, Eko Rudiawan Jamzuri","doi":"10.52158/jacost.v5i1.670","DOIUrl":"https://doi.org/10.52158/jacost.v5i1.670","url":null,"abstract":"This paper discusses the development of desktop applications for traceability systems. The application was developed to facilitate data recording and tracking in an electronics manufacturing company's storage process of Printed Circuit Board (PCB) products. The application is developed using the Visual Basic language and Microsoft Excel databases. Additionally, the application is integrated with a barcode scanner to simplify the data entry process from PCBs and employee ID cards. Through the trial process conducted on the developed application, it has generally functioned in accordance with the development goals. Program control validation has been tested through several application access attempts from users registered as operators and administrators. The application has successfully recorded data from inbound and outbound processes, demonstrating storage and tracking functionality. Furthermore, the application has displayed the actual status data of the PCBs present in the warehouse. In terms of user satisfaction, seven users stated that this application was effective and efficient compared to the manual data recording process previously used by the company. This result was obtained from a questionnaire after the application was implemented in the company warehouse.","PeriodicalId":493006,"journal":{"name":"Journal of Applied Computer Science and Technology","volume":"14 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139808528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deteksi Helm Keselamatan Menggunakan Jetson Nano dan YOLOv7 使用 Jetson Nano 和 YOLOv7 检测安全头盔

Journal of Applied Computer Science and Technology Pub Date : 2024-02-03 DOI: 10.52158/jacost.v5i1.637

Hadi Supriyanto, Sarosa Castrena Abadi, Aliffa Shalsabilah

{"title":"Deteksi Helm Keselamatan Menggunakan Jetson Nano dan YOLOv7","authors":"Hadi Supriyanto, Sarosa Castrena Abadi, Aliffa Shalsabilah","doi":"10.52158/jacost.v5i1.637","DOIUrl":"https://doi.org/10.52158/jacost.v5i1.637","url":null,"abstract":"Increasing awareness of the importance of head personal protective equipment in industrial and construction environments has become a major concern in efforts to improve occupational safety. This research developed an early detection system for the use of computer vision-based head protective equipment using the YOLOv7 model and the Jetson Nano controller. The YOLOv7 algorithm was chosen for its ability for fast and accurate object detection. The YOLOv7 model was trained with a total dataset of 2799 images and iterations of 100 epochs to detect head personal protective equipment with a high degree of accuracy. The system captures imagery, activates a warning alarm, and sends a notification to Telegram when a violation occurs on an object that is not wearing a safety helmet. The test results using the confusion matrix method showed that the developed system was able to detect head personal protective equipment with an accuracy rate of 97.23%, which shows the system's ability to recognize personal protective equipment with very high accuracy. In addition, the system also showed a precision value of 98.71% indicating that all detections performed were correct, and a recall of 95.63% which describes the system's ability to recognize most of the head personal protective equipment available. The average FPS result using GPU with CUDA on Jetson Nano reached 5,723 FPS.","PeriodicalId":493006,"journal":{"name":"Journal of Applied Computer Science and Technology","volume":"32 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139808602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0