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Review of Underwater Image Enhancement Using CNN and U-net 基于CNN和U-net的水下图像增强研究综述
Journal of Artificial Intelligence and Imaging Pub Date : 2023-06-22 DOI: 10.48001/joaii.2023.115-10
Snehal G. Teli, R. Shelke
{"title":"Review of Underwater Image Enhancement Using CNN and U-net","authors":"Snehal G. Teli, R. Shelke","doi":"10.48001/joaii.2023.115-10","DOIUrl":"https://doi.org/10.48001/joaii.2023.115-10","url":null,"abstract":"Due to environmental scattering, images taken in the underwater environment still exhibit color distortion, loss of resolution, and decreased contrast. The suggested study presents a method for enhancing the aesthetic appeal of underwater photography. Yet, because of unwanted staining, decreased contrast, and detail loss brought on by light scattering and absorption, photos that are directly taken in the marine environment are still highly damaged, drastically limiting the amount of information that can be extracted from the image. Thus, acquiring precise and clear photographs is a crucial requirement for aiding scientists in their understanding of the underwater environment. The CNN algorithms are employed in many different applications, including Identification of the object, tracking, recognition, and navigation. Separating the water component from the other component is the most important step here. To get rid of water from a color image, we're suggesting a practical technique.","PeriodicalId":201326,"journal":{"name":"Journal of Artificial Intelligence and Imaging","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132112857","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
Implementation of Simple and Efficient Picture Caption Generator 实现简单高效的图片说明生成器
Journal of Artificial Intelligence and Imaging Pub Date : 2023-06-21 DOI: 10.48001/joaii.2023.1111-18
V. Mane, Riddhi Selkar
{"title":"Implementation of Simple and Efficient Picture Caption Generator","authors":"V. Mane, Riddhi Selkar","doi":"10.48001/joaii.2023.1111-18","DOIUrl":"https://doi.org/10.48001/joaii.2023.1111-18","url":null,"abstract":"Image captioning or picture captioning has become one of the most widely used technologies in applications that generate and provide captions for specific photographs. All these things are done with the help of deep neural networks. It identifies the specific objects in an image and their attributes and relationships. The purpose of this research is to find different things in a photograph, figure out their relationships, and write captions. The proposed system is implemented on dataset Flickr8k along with python. The input images are pre-processed and then features from images are extracted using CNN. To translate the features and objects extracted by CNN to a natural sentence in English LSTM is utilized in the implementation. Different types of images are tested with the proposed system. The results are presented with the generated image captions. The results presented shows the accuracy of the system. The presented method has potentials for such applications where image captioning is essential.","PeriodicalId":201326,"journal":{"name":"Journal of Artificial Intelligence and Imaging","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130675118","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
ANN Based Heart Disease Prognosis 基于神经网络的心脏病预后
Journal of Artificial Intelligence and Imaging Pub Date : 2023-06-21 DOI: 10.48001/joaii.2023.111-4
Kartik G Alur, Shivabharat S Kopparad, Kumbhar Trupti Ravikumar
{"title":"ANN Based Heart Disease Prognosis","authors":"Kartik G Alur, Shivabharat S Kopparad, Kumbhar Trupti Ravikumar","doi":"10.48001/joaii.2023.111-4","DOIUrl":"https://doi.org/10.48001/joaii.2023.111-4","url":null,"abstract":"Heart disease is a major health concern which is responsible for cause of death worldwide. The different factors that cause heart disease includes inadequate blood flow due to fatty plaques in the arteries, stress, family history etc. Early and accurate identification of heart disease can help people take appropriate preventative action, by which the death rate can be reduced. Artificial neural networks (ANNs), have shown good results in different medical applications as they are able to learn complex patterns from the large datasets. An ANN-based models have the capacity to learn intricate patterns from tremendous datasets, thus it is possible to early detection and medication. In this paper, we introduce a machine learning method that makes use of ANNs to predict heart disease utilizing a variety of risk indicators, including age, sex, blood pressure, cholesterol levels, and other important clinical features. The model is trained on this dataset.","PeriodicalId":201326,"journal":{"name":"Journal of Artificial Intelligence and Imaging","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114905516","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
Yoga Pose Trainer and Analyser: Machine Learning (TensorFlow and Open CV) 瑜伽姿势训练器和分析器：机器学习（TensorFlow 和 Open CV）
Journal of Artificial Intelligence and Imaging Pub Date : 2023-06-20 DOI: 10.48001/joaii.2023.1122-24
Shubham Bandgar, Mihir Vanave, Kaivalya Bulbule
{"title":"Yoga Pose Trainer and Analyser: Machine Learning (TensorFlow and Open CV)","authors":"Shubham Bandgar, Mihir Vanave, Kaivalya Bulbule","doi":"10.48001/joaii.2023.1122-24","DOIUrl":"https://doi.org/10.48001/joaii.2023.1122-24","url":null,"abstract":"The \"Yoga Pose Trainer and Analyzer\" is a sophisticated software system designed to enhance the yoga experience for practitioners of all levels. This project combines computer vision, machine learning, and user-friendly interfaces to provide valuable insights and guidance during yoga sessions. Users can interact with the system, receiving real-time feedback on their yoga poses and personalized recommendations to improve their practice. The core functionalities of the system include pose recognition and classification. Using advanced computer vision techniques, the system identifies key points on the user's body and classifies their pose, accurately determining which yoga asana (pose) they are performing. Additionally, users can specify their goals or desired poses, and the system tailors their practice accordingly. The software provides a comprehensive library of yoga poses, offering detailed instructions and highlighting the benefits of each pose. Users can track their progress over time, set goals, and receive guidance on how to achieve their objectives. Safety and privacy considerations are paramount, with the system promoting proper form to prevent injury and ensuring user data security.","PeriodicalId":201326,"journal":{"name":"Journal of Artificial Intelligence and Imaging","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139369228","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
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