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오늘 본 자료
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The relation of multiple-choice cloze items to the Test of English as a Foreign Language
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Trichoblastic Carcinoma Arising from a Nevus Sebaceous
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감정 인식을 위한 멀티모달 모델: Early Fusion과Late Fusion 방식 비교를 중심으로
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한국형발사체 75톤급 액체로켓엔진 감량형 짐벌마운트 개발
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Synthesis and Biological Evaluation of 4-Quinolone Ribosides
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브랜드 확장 시 쾌락적 혹은 실용적 제품과 서비스의 역할에 관한 연구
- 검색키워드
- 저자 : N.Thirupathi Rao (검색결과 7 건)
- 무료
- 기관 내 무료
- 유료
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Latest Technologies used in Industries for Better Production: An Extensive Review
N.Thirupathi Rao,Debnath Bhattacharyya 사단법인 미래융합기술연구학회 2020 아시아태평양융합연구교류논문지 Vol.6 No.6
Technology had grown very fast in recent years in terms of all types of techniques used in various industries. Various types of trends can be observed in almost all sorts of technologies being used in various fields of the market. The utilization of new technology and its trends had become very interesting and making the functioning of the works smoother and more comfortable also reduced the utilization of more man power and reduced the problems faced with manpower. The utilization of such technology trends is giving proper market analysis and also better business processing applications. The trends of the market can be observed or understood within minutes by the utilization of such advanced technologies. In the current article, an attempt has been made to provide the details about the latest technologies and their trend of utilizing in industries for manufacturing and their future scope of development and their utilization in the current day applications.
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Performance Evaluation of Optimized Tandem Communication Network Model
N.Thirupathi Rao 사단법인 미래융합기술연구학회 2019 아시아태평양융합연구교류논문지 Vol.5 No.3
Communication Systems are regulated by a few arbitrary variables. In packetized communication networks, the framework execution is proscribed by entry example and Transmission procedure. In this paper, we presented and break down a two hub correspondence communication network with the suspicion that the arrivals are described by the compound binomial Poisson process. Here, it is additionally expected that the Dynamic data transmission Allocation procedure of transmission is received and the two hubs are associated a pair with stage compose transmission in every hub. The framework execution is investigated by determining the unequivocal articulations for execution measures and numerical delineations. With appropriate cost consideration, the ideal working arrangements of the system are likewise talked about.
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An Extensive Review on Recent Emerging Applications of Artificial Intelligence
B. Harini,N.Thirupathi Rao 사단법인 미래융합기술연구학회 2019 아시아태평양융합연구교류논문지 Vol.5 No.2
In recent days, the applications of artificial intelligence are growing in number by day to day. In the present paper, the authors gave the brief idea about artificial intelligence and the various applications of artificial intelligence. The utilization of artificial intelligence and its related technologies had encouraged and providing various facilities for researchers and scientists to develop and implement the artificial intelligence techniques in various emerging sectors of the market today. As the technology is growing day to day, the utilization of various applications by using the technology is also growing. Hence, the authors gave a clear idea and discussed in detail about the applications of artificial intelligence with the help of some diagrams.
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Voice Playback Detection based on Long-window Scale-factors
U. Nanaji,N. Thirupathi Rao,Ch. Raj Kumar,Debnath Bhattacharyya,Hye-jin Kim 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.12
With the popularity of high fidelity and portable recording device, it becomes very easy for the attacker to spoof speaker verification system by voice playback. In this paper, it found that there exists obvious difference in the scale-factors, a parameter of MP3 codec, when the original and playback voices are compressed by MP3. So, a detection algorithm for the playback voice is proposed. The experimental results show that the detection accuracy of the proposed algorithm can reach to 99.51% for 4 different types of eavesdropping devices. Meanwhile, the algorithm is integrated into the speaker verification system based on GMM-UBM. The equal error rate (EER) of the system has dropped 32% and the system's ability to resist playback attack is improved.
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Hemanth G.,Rao N. Thirupathi 차세대컨버전스정보서비스학회 2021 Journal of Digital Media & Culture Technology Vol.1 No.2
In recent years, breast cancer has emerged as one of the most common types of cancer among women globally. Late diagnosis often results in a higher mortality rate, underlining the crucial need for effective early detection systems, especially those leveraging personal imaging data. In this regard, this study focuses on the integration of transfer learning and deep feature extraction techniques to adapt pretrained CNN models to breast cancer detection. Specifically, AlexNet and VGG16 are employed for feature extraction, with further tuning conducted on AlexNet. The derived features are then classified using Support Vector Machines (SVM). A comprehensive evaluation is carried out using a publicly available breast cancer dataset based on surgical and cellular pathology. Accuracy scores serve as performance metrics. The findings underscore the superior performance of the transfer learning approach compared to the combination of deep feature extraction and SVM classification.
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Detection of Breast Cancer using Deep Learning Techniques
G. Sai Chandrasekhar,Rao N. Thirupathi 차세대컨버전스정보서비스학회 2021 Journal of Digital Media & Culture Technology Vol.1 No.1
Breast cancer poses a global health challenge due to the high false-positive rates associated with traditional mammographic diagnostics. This study introduces a novel model using infrared digital imaging to exploit the thermal difference between healthy and tumorous breasts for early cancer detection. This study employed a Support Vector Machine model and a fine-tuned Deep Neural Network (DNN) to classify thermal images as canceroushealthy, using a dataset of 67 diverse subjects. Images with confidence levels between 0.5 and 0.6 were directed to the SVM for further prediction, improving diagnostic accuracy. The model's utility was validated on a new set of 12 breasts. In this study, the results showcase the potential of infrared imaging in breast cancer detection and suggests improvements in thermal conduction levels and advocating for further model refinement research.
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Debnath Bhattacharyya,Eali Stephen Neal Joshua,N.Thirupathi Rao 한국컴퓨터게임학회 2021 한국컴퓨터게임학회논문지 Vol.34 No.2
In the following years, technology has progressed in so many ways that it has provided the cyber society with a resource that only computers can excel at, such as the art of counterfeit of media, which was before unavailable. Deepfakes are a term used to describe this kind of deception. The majority of well-documented Deep Fakes are produced using Generative Adversarial Network (GAN) Models, which are essentially two distinct Machine Learning Models that perform the roles of attack and defence. These models create and identify deepfakes until they reach a point where the morphing no longer detects the deepfakes anymore. Using this algorithm/model, it is possible to discover and create new media that has a similar demographic to the training set, resulting in the development of the ideal Deep Fake media. Because the alterations are carried out utilising advanced characteristics, they cannot be seen with the human eye. However, it is completely feasible to develop an algorithm that can automatically identify this kind of tampering carried out via the internet. This not only enables us to broaden the scope of our search beyond a single media item, but also beyond a large library of mixed media. The more it learns, the better it becomes as artificial intelligence takes over in full force with automation. In order to create better deep fakes, new models are being developed all the time, making it more difficult to distinguish between genuine and morphing material.
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