Comprehensive Analysis of Face Recognition Technologies by Liu Bowei

“…Additionally, it outlines potential research directions and contributes to the advancement of the field of computer vision.…”
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An Improved PSO Algorithm for Distributed Localization in Wireless Sensor Networks by Dan Li, Xian bin Wen

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Cross‐ethnicity face anti‐spoofing recognition challenge: A review by Ajian Liu, Xuan Li, Jun Wan, Yanyan Liang, Sergio Escalera, Hugo Jair Escalante, Meysam Madadi, Yi Jin, Zhuoyuan Wu, Xiaogang Yu, Zichang Tan, Qi Yuan, Ruikun Yang, Benjia Zhou, Guodong Guo, Stan Z. Li

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RespiroDynamics: A Multifaceted Dataset for Enhanced Lung Health Assessment Using Deep Learning by Ahmed Sharshar, Muhammad Sharshar, Hosam Elhady, Ahmed Aboeitta, Youssef Nafea, Yasser Ashraf, Mohammad Yaqub, Mohsen Guizani

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Peningkatan Performa Ensemble Learning pada Segmentasi Semantik Gambar dengan Teknik Oversampling untuk Class Imbalance by Arie Nugroho, M. Arief Soeleman, Ricardus Anggi Pramunendar, Affandy Affandy, Aris Nurhindarto

“…Segmentasi gambar adalah salah satu bidang dalam computer vision yang membahas bagaimana cara komputer mempelajari dan mengenali segmen dari suatu gambar sesuai label yang ditentukan. …”
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Monocular Depth Estimation: A Review on Hybrid Architectures, Transformers and Addressing Adverse Weather Conditions by Kumara Lakindu, Senanayake Nipuna, Poravi Guhanathan

“…Monocular depth estimation is one of the essential tasks in computer vision as it can provide depth information from 2D images and is extremely beneficial for applications such as autonomous driving, robot navigation, etc. …”
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Siamese comparative transformer-based network for unsupervised landmark detection. by Can Zhao, Tao Wu, Jianlin Zhang, Zhiyong Xu, Meihui Li, Dongxu Liu

“…Landmark detection is a common task that benefits downstream computer vision tasks. Current landmark detection algorithms often train a sophisticated image pose encoder by reconstructing the source image to identify landmarks. …”
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THE REVIEW OF MECHANICAL FAULT DIAGNOSIS METHODS BASED ON CONVOLUTIONAL NEURAL NETWORK by WU DingHai, REN GuoQuan, WANG HuaiGuang, ZHANG YunQiang

“…The Convolutional Neural Network（ CNN） is a classic structure of deep learing and which is being widely and successfully used in the fields of computer vision,target detection,natural language processing,and speech recognition. …”
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Machine learning in medicine: what clinicians should know by Jordan Zheng Ting Sim, Qi Wei Fong, Weimin Huang, Cher Heng Tan

“…Herein, we introduce basic concepts and terms used in AI and ML, and aim to demystify commonly used AI/ML algorithms such as learning methods including neural networks/deep learning, decision tree and application domain in computer vision and natural language processing through specific examples. …”
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A Novel Approach for Detection of Pavement Crack and Sealed Crack Using Image Processing and Salp Swarm Algorithm Optimized Machine Learning by Nhat-Duc Hoang, Thanh-Canh Huynh, Xuan-Linh Tran, Van-Duc Tran

“…Because crack and sealed crack are both line-based defects and may resemble each other in shape, this study puts forward an innovative method based on computer vision for detecting sealed crack and crack. …”
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AN IMPROVED FUZZY K-MEANS CLUSTERING ALGORITHM BASED ON WEIGHT ENTROPY MEASUREMENT AND CALINSKI-HARABASZ INDEX by Nguyễn Như Đồng, Phan Thành Huấn

“…Clustering plays an important role in data mining and is applied widely in fields of pattern recognition, computer vision, and fuzzy control. In this paper, we proposed an improved clustering algorithm combined of both fuzzy k-means using weight Entropy and Calinski-Harabasz index. …”
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s-Goodness for Low-Rank Matrix Recovery by Lingchen Kong, Levent Tunçel, Naihua Xiu

“…Low-rank matrix recovery (LMR) is a rank minimization problem subject to linear equality constraints, and it arises in many fields such as signal and image processing, statistics, computer vision, and system identification and control. …”
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Human Pose Estimation: Single-Person and Multi-Person Approaches by Tang Wan

“…Human pose estimation (HPE), as one of the core tasks in computer vision, plays a crucial role in enabling computers to comprehend human behaviour interactions. …”
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A Scheme Based on Deep Learning for Fruit Classification by Ali Orangzeb Panhwar, Anwar Ali Sathio, Nadeem Manzoor Shah, Sumaira Memon

“…Grading and classifying fruits are critical due to automated machine learning systems. In computer vision, different fruits have large complexity and similarity to identify the fruit types. …”
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A TensorFlow implementation of Local Binary Patterns Transform by Devrim Akgün

“…Direct implementations of such layers in Python may result in long running times, and training a computer vision model may be delayed significantly. For this purpose, TensorFlow framework enables developing accelerated custom operations based on the existing operations which already have support for accelerated hardware such as multicore CPU and GPU. …”
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Digital media use and its effects on digital eye strain and sleep quality in adolescents: A new emerging epidemic? by Merve Şambel Aykutlu, Hasan Cem Aykutlu, Mehmet Özveren, Rüveyde Garip

“…A cross-sectional survey of 512 participants (aged 11-18 years) assessed DES and PSQ using the Computer Vision Syndrome Questionnaire and the Pittsburgh Sleep Quality Index. …”
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Vision-Based Tracking of Uncooperative Targets by Suresh K. Kannan, Eric N. Johnson, Yoko Watanabe, Ramachandra Sattigeri

“…An additional piece of information, the subtended angle, also available from computer vision algorithm is used to improve range estimation accuracy. …”
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Incorporating Colour Information for Computer-Aided Diagnosis of Melanoma from Dermoscopy Images: A Retrospective Survey and Critical Analysis by Ali Madooei, Mark S. Drew

“…Today, clinicians use computer vision in an increasing number of applications to aid early detection of melanoma through dermatological image analysis (dermoscopy images, in particular). …”
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Overview of Sign Language Translation Based on Natural Language Processing by Wang Hanmo

“…This paper explores the progress, challenges, and future directions in Sign Language Translation (SLT) within the broader field of Sign Language Processing (SLP), which combines Computer Vision (CV) and Natural Language Processing (NLP) to translate sign language videos into spoken language texts. …”
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Inception neural network for human activity recognition using wearable sensor by Duo CHAI, Cheng XU, Jie HE, Shao-yang ZHANG, Shi-hong DUAN, Yue QI

“…The experience from computer vision was learned,an innovative neural network model called InnoHAR (inception neural network for human activity recognition) based on the inception neural network and recurrent neural network was put forward,which started from an end-to-end multi-channel sensor waveform data,followed by the 1×1 convolution for better combination of the multi-channel data,and the various scales of convolution to extract the waveform characteristics of different scales,the max-pooling layer to prevent the disturbance of tiny noise causing false positives,combined with the feature of GRU helped to time-sequential modeling,made full use of the characteristics of data classification task.Compared with the state-of-the-art neural network model,the InnoHAR model has a promotion of 3% in the recognition accuracy,which has reached the state-of-the-art on the dataset we used,at the same time it still can guarantee the real-time prediction of low-power embedded platform,also with more space for future exploration.…”
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