An Evaluation of Deep Learning Methods for Small Object Detection by Nhat-Duy Nguyen, Tien Do, Thanh Duc Ngo, Duy-Dinh Le

“…Small object detection is an interesting topic in computer vision. With the rapid development in deep learning, it has drawn attention of several researchers with innovations in approaches to join a race. …”
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A Novel Framework for Automation Technology Based on Machine Vision and Robotics in Electrical Power Inspection Processing by Heng Zhao, Shengnan Hu, Qingmiao Chen, Jiagui Tao, Jianzhuo Dai

“…As a well-known support, computer vision is a powerful factor to improve the application and development of the electronic system. …”
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FAB: Fast Angular Binary Descriptor for Matching Corner Points in Video Imagery by Mehwish Tahir, Nadia Kanwal, Fatima Anjum

“…Image matching is a fundamental step in several computer vision applications where the requirement is fast, accurate, and robust matching of images in the presence of different transformations. …”
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LEHP-DETR: A model with backbone improved and hybrid encoding innovated for flax capsule detection by Changshun Wang, Junying Han, Chengzhong Liu, Jianping Zhang, Yanni Qi

“…The development of computer vision and deep learning techniques offers a new way to solve this problem. …”
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A Comprehensive Review of Facial Beauty Prediction Using Multi-task Learning and Facial Attributes by Ali H. Ibrahem, Adnan M. Abdulazeez

“… Beauty multi-task prediction from facial attributes is a multidisciplinary challenge at the intersection of computer vision, machine learning, and psychology. Despite the centrality of beauty in human perception, its subjective nature—shaped by individual, social, and cultural influences—complicates its computational modeling. …”
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The role of chromatin state in intron retention: A case study in leveraging large scale deep learning models. by Ahmed Daoud, Asa Ben-Hur

“…Complex deep learning models trained on very large datasets have become key enabling tools for current research in natural language processing and computer vision. By providing pre-trained models that can be fine-tuned for specific applications, they enable researchers to create accurate models with minimal effort and computational resources. …”
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A human single-neuron dataset for object recognition by Runnan Cao, Peter Brunner, Nicholas J. Brandmeir, Jon T. Willie, Shuo Wang

“…We employed two sets of naturalistic object images from leading datasets extensively used in primate neural recordings and computer vision models: we recorded 1204 neurons using the ImageNet stimuli, which included broader object categories (10 different images per category for 50 categories), and we recorded 512 neurons using the Microsoft COCO stimuli, which featured a higher number of images per category (50 different images per category for 10 categories). …”
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Advancing semantic segmentation: Enhanced UNet algorithm with attention mechanism and deformable convolution. by Effat Sahragard, Hassan Farsi, Sajad Mohamadzadeh

“…This paper presents a novel method for improving semantic segmentation performance in computer vision tasks. Our approach utilizes an enhanced UNet architecture that leverages an improved ResNet50 backbone. …”
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Advancements in CNN Architectures for Offline Handwritten Arabic Character Recognition by El Ibrahimi Aissam, Elzaar Abdellah, El Akchioui Nabil, Benaya Nabil, El Allati Abderrahim

“…The recognition of handwritten Arabic characters not only preserves the integrity of the Arabic language but also enhances computer vision applications tailored for Arabic script. …”
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Video-based estimation of blood pressure. by Ananyananda Dasari, Laszlo A Jeni, Conrad S Tucker

“…We utilize a combination of computer vision techniques and demographic information (such as the height and the weight of the subject) to capture and incorporate the aforementioned subject specific blood vessel parameters into our estimation of blood pressure. …”
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Modified Particle Swarm Optimization on Feature Selection for Palm Leaf Disease Classification by Veri Julianto, Ahmad Rusadi Arrahimi, Oky Rahmanto, Mohammad Sofwat Aldi

“…This study explores the application of artificial intelligence, specifically computer vision and machine learning, for disease detection. …”
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An Experimental Validation of Phase-Based Motion Magnification for Structures with Developing Cracks and Time-Varying Configurations by M. Civera, L. Zanotti Fragonara, P. Antonaci, G. Anglani, C. Surace

“…In this study, Computer Vision and Phase-Based Motion Magnification (PBMM) are validated for continuous Structural Health Monitoring (SHM) purposes. …”
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The use of technical vision in flexible production systems to determine coordinates of randomly located objects by K. V. Averkov, D. S. Makashin

“…The article is devoted to the development of an object recognition algorithm using technical vision using Python and the OpenCV computer vision library. The article presents a program that allows you to set the coordinates of an object arbitrarily located in the field of view of the camera, as well as determine its orientation. …”
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A Fall Risk Detection Model for Infants While Sleeping based on Convolutional Neural Networks by Acep Hendra, Handoko Supeno

“…As an alternative, computer vision techniques have shown rapid advancements in recent years, with Convolutional Neural Networks (CNNs) proving to be highly effective in recognizing visual patterns, including human motion and posture detection. …”
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DR_PVNet: An Improved PVNet Network for Weakly Textured Object Pose Estimation in Indoor Complex Environments by Mengru Niu, Changyong Li

“…6D pose estimation of objects is an essential task in computer vision. However, estimating the 6D pose of a weakly textured object from an image is challenging due to the occluded environment and the weakly textured appearance. …”
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Keratoconus disease classification with multimodel fusion and vision transformer: a pretrained model approach by Shokufeh Yaraghi, Toktam Khatibi

“…These models have been trained on large datasets and have demonstrated strong performance in various computer vision tasks.The extracted features from the three pretrained models were fused using a feature fusion technique. …”
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Enhancing zero-shot relation extraction with a dual contrastive learning framework and a cross-attention module by Diyou Li, Lijuan Zhang, Jie Huang, Neal Xiong, Lei Zhang, Jian Wan

“…Moreover, the cross-attention network of our model is introduced from the computer vision field to enhance the attention paid by the input instance to the relevant information of the relation description. …”
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Unveiling the Complexity of Medical Imaging through Deep Learning Approaches by Javaid Iqbal Bhat, Novsheena Rasool

“…Specifically, an in-depth discussion is conducted on the Convolutional Neural Network (CNN) owing to its widespread adoption as a paramount tool in computer vision tasks. Moreover, an exhaustive exploration encompasses deep learning classification approaches, procedural aspects of medical image processing, as well as a thorough examination of key features and characteristics. …”
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Image Dehazing Based on Improved Color Channel Transfer and Multiexposure Fusion by Shaojin Ma, Weiguo Pan, Hongzhe Liu, Songyin Dai, Bingxin Xu, Cheng Xu, Xuewei Li, Huaiguang Guan

“…Image dehazing is one of the problems that need to be solved urgently in the field of computer vision. In recent years, more and more algorithms have been applied to image dehazing and achieved good results. …”
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Research status and development trends of dust concentration monitoring technology by ZHANG Yongqi, WANG Jie, ZHOU Yuhao, YANG Junni, DENG Bin

“…It is proposed that future efforts should be dedicated to integrating dust concentration monitoring technologies with emerging technologies such as machine learning, deep learning, computer vision, and big data analysis and prediction. …”
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