DeepThink IoT: the strength of deep learning in internet of things
Abstract The integration of Deep Learning (DL) and the Internet of Things (IoT) has
revolutionized technology in the twenty-first century, enabling humans and machines to …
revolutionized technology in the twenty-first century, enabling humans and machines to …
Fine-grained visual classification via progressive multi-granularity training of jigsaw patches
Fine-grained visual classification (FGVC) is much more challenging than traditional
classification tasks due to the inherently subtle intra-class object variations. Recent works …
classification tasks due to the inherently subtle intra-class object variations. Recent works …
The devil is in the channels: Mutual-channel loss for fine-grained image classification
The key to solving fine-grained image categorization is finding discriminate and local
regions that correspond to subtle visual traits. Great strides have been made, with complex …
regions that correspond to subtle visual traits. Great strides have been made, with complex …
Deep learning serves traffic safety analysis: A forward‐looking review
This paper explores deep learning (DL) methods that are used or have the potential to be
used for traffic video analysis, emphasising driving safety for both autonomous vehicles and …
used for traffic video analysis, emphasising driving safety for both autonomous vehicles and …
BSNet: Bi-similarity network for few-shot fine-grained image classification
Few-shot learning for fine-grained image classification has gained recent attention in
computer vision. Among the approaches for few-shot learning, due to the simplicity and …
computer vision. Among the approaches for few-shot learning, due to the simplicity and …
Progressive learning of category-consistent multi-granularity features for fine-grained visual classification
Fine-grained visual classification (FGVC) is much more challenging than traditional
classification tasks due to the inherently subtle intra-class object variations. Recent works …
classification tasks due to the inherently subtle intra-class object variations. Recent works …
Deep reinforcement learning-based energy management for a series hybrid electric vehicle enabled by history cumulative trip information
It is essential to develop proper energy management strategies (EMSs) with broad
adaptability for hybrid electric vehicles (HEVs). This paper utilizes deep reinforcement …
adaptability for hybrid electric vehicles (HEVs). This paper utilizes deep reinforcement …
UAV autonomous target search based on deep reinforcement learning in complex disaster scene
In recent years, artificial intelligence has played an increasingly important role in the field of
automated control of drones. After AlphaGo used Intensive Learning to defeat the World Go …
automated control of drones. After AlphaGo used Intensive Learning to defeat the World Go …
Dynamic service function chain embedding for NFV-enabled IoT: A deep reinforcement learning approach
The Internet of things (IoT) is becoming more and more flexible and economical with the
advancement in information and communication technologies. However, IoT networks will …
advancement in information and communication technologies. However, IoT networks will …
Intelligent traffic-monitoring system based on YOLO and convolutional fuzzy neural networks
CJ Lin, JY Jhang - IEEE Access, 2022 - ieeexplore.ieee.org
With the rapid pace of urbanization, the number of vehicles traveling between cities has
increased significantly. Consequently, many traffic-related problems have emerged, such as …
increased significantly. Consequently, many traffic-related problems have emerged, such as …