Use of Augmented Reality for Training Assistance in Laparoscopic Surgery: Scoping Literature Review by Francisco Javier Celdrán, Javier Jiménez-Ruescas, Carlos Lobato, Lucía Salazar, Juan Alberto Sánchez-Margallo, Francisco M Sánchez-Margallo, Pascual González

“…It underscores the potential of emerging technologies such as haptic feedback, computer vision, and eye tracking to further enhance laparoscopic skill acquisition. …”
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Research progress and trends of deep learning based wireless communication receiving method by Panpan LI, Zhengxia XIE, Guangxue YUE, Xin LIU

“…With the continues expansion of the application boundary for wireless communications, the application environment of wireless communications is becoming increasingly complex and diverse, which faces negative impacts such as radio frequency (RF) damage, channel fading, interference and noise.It brings difficulties to recover the original information at the receiver.Drawing from the research results of deep learning methods in computer vision, pattern recognition, natural language processing and other fields, wireless communication reception technology based on deep learning has received wide attentions from both academia and industry.Firstly, the current research status of wireless communication reception technology based on deep learning at home and abroad was described.Secondly, the current technical challenges of wireless communication reception in the context of signal big data were outlined, and a reference architecture of intelligent wireless communication reception based on deep neural network was proposed.Finally, the development trend of intelligent wireless communication reception method in the context of signal big data was discussed.It is expected to provide reference for the research and development of wireless communication technology based on deep learning.…”
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Identifying the Origin of Cyber Attacks Using Machine Learning and Network Traffic Analysis by Du Tianqing

“…In this paper, PCAP refers to Packet Capture, Network Intrusion Detection Systems refers to NIDS, Artificial Intelligence refers to AI, machine learning refers to ML, Computer Vision refers to CV, and Natural Language Processing refers to NLP. …”
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Learning-Based Dark and Blurred Underwater Image Restoration by Yifeng Xu, Huigang Wang, Garth Douglas Cooper, Shaowei Rong, Weitao Sun

“…Underwater image processing is a difficult subtopic in the field of computer vision due to the complex underwater environment. …”
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Epipolar Plane Image Rectification and Flat Surface Detection in Light Field by Lipeng Si, Hao Zhu, Qing Wang

“…Flat surface detection is one of the most common geometry inferences in computer vision. In this paper we propose detecting printed photos from original scenes, which fully exploit angular information of light field and characteristics of the flat surface. …”
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Swin Transformer lightweight: an efficient strategy that combines weight sharing, distillation and pruning by HAN Bo, ZHOU Shun, FAN Jianhua, WEI Xianglin, HU Yongyang, ZHU Yanping

“…Swin Transformer, as a layered visual transformer with shifted windows, has attracted extensive attention in the field of computer vision due to its exceptional modeling capabilities. …”
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Adaptive Refinement of Segmented Object Contour Based on the Brightness of Neighboring Pixels Using the Ensemble Method by Vladyslav D. Koniukhov

“…Improving the accuracy of computer vision algorithms plays a significant role in the tasks of medical image segmentation. …”

IRSnet: An Implicit Residual Solver and Its Unfolding Neural Network With 0.003M Parameters for Total Variation Models by Yuanhao Gong

“…Solving total variation problems is fundamentally important for many computer vision tasks, such as image smoothing, optical flow estimation and 3D surface reconstruction. …”
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Machine learning and facial recognition for down syndrome detection: A comprehensive review by Khosro Rezaee

“…Traditionally diagnosed through clinical assessments, Down syndrome, a genetic disorder characterized by distinctive facial features, has benefited from recent advancements in computer vision and artificial intelligence (AI). This paper explores various facial analysis techniques, including deep convolutional neural networks (DCNNs) and hybrid models combining traditional image processing with deep learning. …”
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A Comprehensive Survey of Machine Learning Techniques and Models for Object Detection by Maria Trigka, Elias Dritsas

“…Object detection is a pivotal research domain within computer vision, with applications spanning from autonomous vehicles to medical diagnostics. …”
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Enhanced Asymmetric Bilinear Model for Face Recognition by Wenjuan Gong, Weishan Zhang, Jordi Gonzàlez, Yan Ren, Zhen Li

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Evaluation of Natural Image Generation and Reconstruction Capabilities Based on the β-VAE Model by Zhang Honghao

“…Natural image generation models are crucial in computer vision. However, the Variational Autoencoder (VAE) has limitations in image quality and diversity, while β-VAE achieves a balance between the decoupling of latent space and generative quality by adjusting the coefficient β. …”
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Advancements in Image Classification: From Machine Learning to Deep Learning by Cheng Haoran

“…Image classification, as an essential task within the realm of computer vision, has evolved from traditional machine learning methods to deep learning techniques. …”
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Envisioning Archival Images with Artificial Intelligence by Jessica Bushey

“…The review highlights the potential of AI, particularly computer vision (CV), to address the challenges associated with processing large volumes of digital images. …”
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Fully Kernected Neural Networks by Wei Zhang, Zhi Han, Xiai Chen, Baichen Liu, Huidi Jia, Yandong Tang

“…DCNNs have achieved significant improvement in many computer vision tasks. For an image classification task, the accuracy comes to saturation when the depth and width of network are enough and appropriate. …”
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Multidisciplinary ML Techniques on Gesture Recognition for People with Disabilities in a Smart Home Environment by Christos Panagiotou, Evanthia Faliagka, Christos P. Antonopoulos, Nikolaos Voros

“…In this paper, three methods for gesture recognition and computer vision were implemented and tested in order to investigate the most suitable one. …”
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A Modified Fully Convolutional Network for Crack Damage Identification Compared with Conventional Methods by Meng Meng, Kun Zhu, Keqin Chen, Hang Qu

“…With the development of artificial intelligence especially the combination of deep learning and computer vision, greater advantages have been brought to the concrete crack detection based on convolutional neural network (CNN) over the traditional methods. …”
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Automatic Identification and Location of Tunnel Lining Cracks by Pengyu Wang, Shuhong Wang, Alipujiang Jierula

“…It is a new trend to use computer vision to detect tunnel cracks over the past few years in China and foreign countries. …”
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STABILITY CONTROL MODELLING UNDER DYNAMIC MOTION SCENARIO OF A DIFFERENTIAL DRIVE ROBOT by ADEDOTUN O. OWOJORI, KAYODE F. AKINGBADE, WALIU O. APENA, ERASTUS O. OGUNTI

“…Signal analysis and computer vision techniques serve as leverage to make the design achievable. …”
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The Interactive Design of Library Information Sharing in View of Network Communication Technology by Yeping Zhen

“…Understanding the audience’s psychology and behavior characteristics can effectively enhance computer vision interaction and expand the scope of the audience. …”
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