A comprehensive and systematic look up into deep learning based object detection techniques: A review
Object detection can be regarded as one of the most fundamental and challenging visual
recognition task in computer vision and it has received great attention over the past few …
recognition task in computer vision and it has received great attention over the past few …
Fine-grained image analysis with deep learning: A survey
Fine-grained image analysis (FGIA) is a longstanding and fundamental problem in computer
vision and pattern recognition, and underpins a diverse set of real-world applications. The …
vision and pattern recognition, and underpins a diverse set of real-world applications. The …
A survey of deep learning-based object detection
Object detection is one of the most important and challenging branches of computer vision,
which has been widely applied in people's life, such as monitoring security, autonomous …
which has been widely applied in people's life, such as monitoring security, autonomous …
Boosting few-shot fine-grained recognition with background suppression and foreground alignment
Few-shot fine-grained recognition (FS-FGR) aims to recognize novel fine-grained categories
with the help of limited available samples. Undoubtedly, this task inherits the main …
with the help of limited available samples. Undoubtedly, this task inherits the main …
Sim-trans: Structure information modeling transformer for fine-grained visual categorization
Fine-grained visual categorization (FGVC) aims at recognizing objects from similar
subordinate categories, which is challenging and practical for human's accurate automatic …
subordinate categories, which is challenging and practical for human's accurate automatic …
MVF-Net: A multi-view fusion network for event-based object classification
Event-based object recognition has drawn increasing attention for event cameras'
distinguished advantages of low power consumption and high dynamic range. For this new …
distinguished advantages of low power consumption and high dynamic range. For this new …
Cross-part learning for fine-grained image classification
Recent techniques have achieved remarkable improvements depended on mining subtle
yet distinctive features for fine-grained visual classification (FGVC). While prior works directly …
yet distinctive features for fine-grained visual classification (FGVC). While prior works directly …
Three-dimensional indoor localization and tracking for mobile target based on WiFi sensing
J Ding, Y Wang, H Si, S Gao… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
With the prevalence of commodity WiFi devices and development of the Internet of Things
(IoT), the usage of WiFi has been extended from communication to context aware. Based on …
(IoT), the usage of WiFi has been extended from communication to context aware. Based on …
Explainable deep-learning-assisted sweat assessment via a programmable colorimetric chip
Z Liu, J Li, J Li, T Yang, Z Zhang, H Wu, H Xu… - Analytical …, 2022 - ACS Publications
Multianalytes and individual differences of biofluids (such as blood, urine, or sweat) pose
enormous complexity and challenges to rapid, facile, high-throughput, and accurate clinical …
enormous complexity and challenges to rapid, facile, high-throughput, and accurate clinical …
Complementary parts contrastive learning for fine-grained weakly supervised object co-localization
L Ma, F Zhao, H Hong, L Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The aim of weakly supervised object co-localization is to locate different objects of the same
superclass in a dataset. Recent methods achieve impressive co-localization performance by …
superclass in a dataset. Recent methods achieve impressive co-localization performance by …