Search Results - image processing methods

Robust Image Steganography Approach Based on Edge Detection Combined With CNN Algorithm by Rana Al-Rawashdeh, Md Mahfuzur Rahman, Mahmood Niazi

“…Firstly, the edges in the cover image are identified using a suitable edge detection method (i.e., using the canny or sobel algorithm), and then the secret data is embedded inside the edge-detected cover image using a deep learning approach, and finally, the created stego image is sent to the receiver. …”
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Image-Based Malicious Network Traffic Detection Framework: Data-Centric Approach by Doo-Seop Choi, Taeguen Kim, Boojoong Kang, Eul Gyu Im

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Self-Supervised Keypoint Learning for the Geometric Analysis of Road-Marking Templates by Chayanon Sub-r-pa, Rung-Ching Chen

“…However, traditional feature-based methods struggle with templates that feature simple geometries and lack rich textures, making reliable feature matching and alignment difficult, even under controlled conditions. …”
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Multi-Focus Image Fusion Based on Dual-Channel Rybak Neural Network and Consistency Verification in NSCT Domain by Ming Lv, Sensen Song, Zhenhong Jia, Liangliang Li, Hongbing Ma

“…Some existing methods suffer from misjudgment of focus areas, resulting in incorrect focus information or the unintended retention of blurred regions in the fused image. …”
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Creation of a Dataset of MSCT-Images and Clinical Data for Acute Cerebrovascular Events by F. A. Sharifullin, D. D. Dolotova, T. G. Barmina, S. S. Petrikov, L. S. Kokov, G. R. Ramazanov, Y. R. Blagosklonova, I. V. Arkhipov, I. M. Skorobogach, N. N. Cheremushkin, V. V. Donitova, B. A. Kobrinski, A. V. Gavrilov

“…Background The use of neuroimaging methods is an integral part of the process of assisting patients with acute cerebrovascular events (ACVE), and computed tomography (CT) is the «gold standard» for examining this category of patients. …”
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Interferometric techniques for virtual histology and staining: principles, techniques, and applications in biomedical imaging by Mohammadhossein Salimi, Bahman Vahidi

“…Results: Interferometric methods deliver high-resolution, depth-resolved, and label-free imaging of tissues in both in-vivo and ex-vivo contexts. …”
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Discovery of EP4 antagonists with image-guided explainable deep learning workflow by Ma Pengsen, Cheng Zhiyuan, Cheng Zhixiang, Wang Yijie, Chai Xiaolei, Feng Bo, Xiang Hongxin, Zeng Li, Liu Xueming, Li Pengyong, Wei Leyi, Zou Quan, Liu Mingyao, Zeng Xiangxiang, Lu Weiqiang

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DETERMINATION OF THE BEST OPTIMIZER FOR A NEURONETWORK IN THE DEVELOPMENT OF AUTOMATIC IMAGE TAGGING SYSTEMS by Andrian Kozynets

“…Choosing the best optimizer is an important step in developing efficient automatic image classification systems. In particular, for neural networks based on convolutional neural networks (CNNs), the choice between popular optimization methods such as Adam (Adaptive Moment Estimation) and SGD (Stochastic Gradient Descent, SGD) can significantly affect their performance. …”
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Adaptive Context-Aware Generative Adversarial Network for Low-quality Image Enhancement by Xingyu Pan, Fengling Chen

“…However, current methods still face with two issues: (1) They commonly earn a deterministic generation mapping between low-quality and normal images via relying on pixel-level reconstruction, leading to improper brightness and noise in the enhancing process. (2) They use only one type of generative model, either explicit or implicit, which limits flexibility and efficiency of models. …”
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Super-Resolution Imaging Through Scattering Medium Based on Parallel Compressed Sensing by Yao Zhao, Qian Chen, Shenghang Zhou, Guohua Gu, Xiubao Sui

“…However, traditional methods implemented measurement matrix by digital mirror device (DMD) or spatial light modulator, which is a serial imaging process and makes the method inefficient. …”
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Combined Application of Deep Learning and Radiomic Features for Classification of Lung CT Images by Shariati Faridoddin, V. A. Pavlov

“…The use of a convolutional neural network enabled large volumes of data to be processed, surpassing the performance of conventional methods. …”
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Efficient Single-Exposure Holographic Imaging via a Lightweight Distilled Strategy by Jiaosheng Li, Haoran Liu, Zeyu Lai, Yifei Chen, Chun Shan, Shuting Zhang, Youyou Liu, Tude Huang, Qilin Ma, Qinnan Zhang

“…Digital holography can capture and reconstruct 3D object information, making it valuable for biomedical imaging and materials science. However, traditional holographic reconstruction methods require the use of phase shift operation in the time or space domain combined with complex computational processes, which, to some extent, limits the range of application areas. …”
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Facial Emotion Images Recognition Based On Binarized Genetic Algorithm-Random Forest by Murad Ibrahim Husin Alzawali, Yusliza Yusoff, Razana Alwee, Zuriahati Mohd Yunos, Mohamad Shukor Talib, Haswadi Hassan, Fahad Taha AL-Dhief, Musatafa Abbas Abbood Albadr, Majid Razaq Mohamed Alsemawi, Sharifah Zarith Rahmah Syed Ahmad

“…Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. …”
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Spine inflammatory changes in patients with ankylosing spondylitis assessed by magnetic resonance image by A G Bochkova, A. V. Levshakova, N. I. Bunchuk

“…IL scoring was done only in 29 pts evaluated in both sagittal and axial planes. We used two scoring methods: 1) individual IL score of the each spine element (vertebral bodies, processes, arches, zygapophyseai, costovertebral and costotransverse joints, ligaments), and 2) separate IL scoring in the vertebral bodies and posterior spinal elements in order "yes/no”. …”
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USA propaganda in Cold War period: formation of the image of enemy in face of the USSR by Vadym Bespeka

“…The proposed study attempts to differentiate itself from Soviet and post-Soviet sources of information and, based solely on US publications, to identify the main cliches formed in the US information space regarding the image of the enemy in the face of the USSR.…”
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Industrial Computed Tomography Image Denoising Network Based on Channel Attention Mechanism by Yu HE, Chengxiang WANG, Wei YU

“…To improve the quality of low signal-to-noise CT reconstructed images, this study proposes a deep learning-based denoising method. …”
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Polarization Imaging Descattering Based on Dark Channel Prior Background Light Estimation by Jiarui Zhang, Yaxin Cai, Ming Fang

“…In turbid water environments, conventional polari-metric imaging descattering methods usually rely on selecting a non-target background region as a substitute for global back-ground light information, leading to image clarity. …”
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Removing Scattered Light in Biomedical Images via Total Variation Guided Filter by Yuanhao Gong

“…This is fundamentally different from the case in natural images where the ground truth is available. Second, although some neural network methods can remove the scattered light in biomedical images, they contain a large number of parameters, hampering their training process and the deployment in practical applications. …”
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The Possibilities of Magnetic Resonance Imaging in the Diagnosis of Microstructural Changes of the Subchondral Bone in Osteoarthritis by M. A. Kabalyk

“…The revealed regularity of the change in the relaxation time spectrum of T2-images reflects the degenerative process in subchondral bone with osteoarthritis.…”
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Deep convolution neural network model in problem of crack segmentation on asphalt images by B. V. Sobol, A. N. Soloviev, P. V. Vasiliev, L. A. Podkolzina

“…Thus, it is necessary to improve the conditional assessment schemes of the monitor objects through the autovision.Materials and Methods. The authors have proposed a model of a deep convolution neural network for identifying defects on the road pavement images. …”
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