This paper describes the design of smart village that can be describe as an indicator for the smart village in Indonesia, where the Indonesian population is now more than 250 million peoples. with several islands as m...
详细信息
Traveling has become a part of life at the time of the current urbanization. The growth rate of the internet and the availability of information allows travellers to access tourist information easier and faster. Howev...
详细信息
Sign language Recognition is the study to help bridging communication of deaf-mute people. Sign Language Recognition uses techniques to convert gestures of sign language into words or alphabet. In Indonesia, there are...
详细信息
The cardiac muscle is elastic and deformable. Pushing a catheter in contact with the cardiac muscle surface to conduct focal energy-based ablative therapies, such as RF ablation, requires an adequate electrode-tissue ...
详细信息
作者:
Ximenes, PabloMello, Patricia
School of Cybersecurity and Privacy College of Computing Atlanta United States
Computer Science Graduate Program Fortaleza Brazil
This paper uses the Diamond Model of intrusion analysis to discuss the intricacies and unfoldings of the cyberattack that enabled Operation 'Car Wash' leak (nicknamed 'VazaJato'), one of the most signi...
详细信息
This study evaluates the performance of the REAL-ESRGAN [1] model on images with varying levels of degradation using the DIV2K dataset [2], such as the Wild, the Mild, the Difficult, and the x8 subsets. REAL-ESRGAN wa...
详细信息
ISBN:
(数字)9798350389654
ISBN:
(纸本)9798350389661
This study evaluates the performance of the REAL-ESRGAN [1] model on images with varying levels of degradation using the DIV2K dataset [2], such as the Wild, the Mild, the Difficult, and the x8 subsets. REAL-ESRGAN was created to solve super-resolution problems and aims to produce high-resolution images from low-resolution images. Experiments were conducted at scales of x2 and x4, and performance was measured using Full-Reference metrics (LPIPS, PSNR, SSIM) and No-Reference metrics (NIQE, MANIQA, CLIPIQA, and PI). The Results were good, especially with the x2 scale; it has higher PSNR and SSIM scores, lower LPIPS and NIQE values, and enhanced visual and perceptual quality. The model faced more significant challenges with the wild and the difficult datasets because they have more complex degradations and compression artifacts; it can be seen with unstable results of Full-Reference and No-Reference metrics. On the contrary, the Mild and x8 datasets yielded better results in both metrics; not only that, even the computational cost for Mild and x8 outperforms the rest of the dataset. This study shows the strengths and limitations of REAL-ESRGAN in handling different levels of image degradation. For future research, the model needs enhancement to tackle the degradation format of the wild and the difficult dataset. It would be good if the REAL-ESRGAN improvement could also maintain the computational cost.
Sports analytics have become an important part in the improvement of athlete performances in the last decade. Badminton is one such sport where sports analytics can prove beneficial for its athletes. By incorporating ...
详细信息
Medical imaging abnormality detection is challenging, but deep learning approaches have shown promise. This paper reviews the current state of the art in deep learning approaches for detecting abnormalities in chest m...
Medical imaging abnormality detection is challenging, but deep learning approaches have shown promise. This paper reviews the current state of the art in deep learning approaches for detecting abnormalities in chest medical imaging. To discover the trends, opportunities, and challenges associated with this field, 18 studies were selected from Google Scholar based on their titles, abstracts, and contents for extensive review to answer two research questions. The study found that the National Institutes of Health (NIH) Chest X-ray 14 dataset is the most used dataset for this task. Most research uses a single-modal approach, considering only image data as input, with X-ray being the more popular instrument. There are 8 out of 18 studies leverage the transfer learning approach, with ResN et50 being the most popular network. MobileNetV2 has demonstrated competitive results compared to more robust networks. Preprocessing techniques such as image enhancement and data augmentation are leveraged by 61.1 % of the reviewed studies and are shown to improve model performance.
In offshore aquaculture operations, personnel equipped with diving gear are often necessary to inspect the underwater net cages for damage, particularly on the sea floor. This manual inspection process is time-consumi...
详细信息
ISBN:
(数字)9798331530839
ISBN:
(纸本)9798331530846
In offshore aquaculture operations, personnel equipped with diving gear are often necessary to inspect the underwater net cages for damage, particularly on the sea floor. This manual inspection process is time-consuming and complex. To overcome this problem, this paper proposes a computer vision solution for identifying damage in underwater net cages to address the inefficiencies and challenges of traditional manual inspections. The proposed scheme utilizes a high-performance multi-branch computational architecture designed based on ShuffleNet architecture to detect net cage damage more efficiently. Experimental results demonstrate that this work performs well on the ImageNet ILSVRC-2010 dataset and achieves an accuracy of 88.54% in underwater net damage detection.
Higher education worldwide has adopted Video-Based Learning (VBL) over the past decade. They have tried to build a VBL system to improve services to students. However, the researcher's topic was not fully explored...
详细信息
暂无评论