Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
A comprehensive review of object detection with deep learning
R Kaur, S Singh - Digital Signal Processing, 2023 - Elsevier
In the realm of computer vision, Deep Convolutional Neural Networks (DCNNs) have
demonstrated excellent performance. Video Processing, Object Detection, Image …
demonstrated excellent performance. Video Processing, Object Detection, Image …
Object detection using deep learning, CNNs and vision transformers: A review
Detecting objects remains one of computer vision and image understanding applications'
most fundamental and challenging aspects. Significant advances in object detection have …
most fundamental and challenging aspects. Significant advances in object detection have …
Towards large-scale small object detection: Survey and benchmarks
With the rise of deep convolutional neural networks, object detection has achieved
prominent advances in past years. However, such prosperity could not camouflage the …
prominent advances in past years. However, such prosperity could not camouflage the …
Mpdiou: a loss for efficient and accurate bounding box regression
S Ma, Y Xu - arxiv preprint arxiv:2307.07662, 2023 - arxiv.org
Bounding box regression (BBR) has been widely used in object detection and instance
segmentation, which is an important step in object localization. However, most of the existing …
segmentation, which is an important step in object localization. However, most of the existing …
Enhancing geometric factors in model learning and inference for object detection and instance segmentation
Deep learning-based object detection and instance segmentation have achieved
unprecedented progress. In this article, we propose complete-IoU (CIoU) loss and Cluster …
unprecedented progress. In this article, we propose complete-IoU (CIoU) loss and Cluster …
Detectors: Detecting objects with recursive feature pyramid and switchable atrous convolution
Many modern object detectors demonstrate outstanding performances by using the
mechanism of looking and thinking twice. In this paper, we explore this mechanism in the …
mechanism of looking and thinking twice. In this paper, we explore this mechanism in the …
Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection
Object detection has been dominated by anchor-based detectors for several years.
Recently, anchor-free detectors have become popular due to the proposal of FPN and Focal …
Recently, anchor-free detectors have become popular due to the proposal of FPN and Focal …
Convolutional neural network: a review of models, methodologies and applications to object detection
A Dhillon, GK Verma - Progress in Artificial Intelligence, 2020 - Springer
Deep learning has developed as an effective machine learning method that takes in
numerous layers of features or representation of the data and provides state-of-the-art …
numerous layers of features or representation of the data and provides state-of-the-art …
A review of object detection based on deep learning
With the rapid development of deep learning techniques, deep convolutional neural
networks (DCNNs) have become more important for object detection. Compared with …
networks (DCNNs) have become more important for object detection. Compared with …
Deep high-resolution representation learning for visual recognition
High-resolution representations are essential for position-sensitive vision problems, such as
human pose estimation, semantic segmentation, and object detection. Existing state-of-the …
human pose estimation, semantic segmentation, and object detection. Existing state-of-the …