With the dawn of Industry 5.0 upon us, the smart factory emerges as a pivotal element, playing a crucial role in the realm of intelligent manufacturing. Meanwhile, mobile edge computing is proposed to alleviate the computational burden presented ...

Demand Response (DR) has become a key strategy for enhancing energy system sustainability and reducing costs. Deep Learning (DL) has emerged as crucial for managing DR's complexity and large data volumes, enabling near real-time decision-making. ...

With the construction of intelligent grids, unmanned aerial vehicle have been widely employed to inspect transmission lines. The inspection process generates a large amount of data, which requires a lightweight model to reduce computational ...

In this paper, we propose a semantic segmentation framework for panoramic images. First, in order to solve the problem of large panoramic image size, we use HarDNet in the backbone. By applying HarDNet, while improving segmentation accuracy, it ...

Object detection in unmanned aerial vehicle (UAV) images presents challenges such as high altitudes, small object sizes, and complex backgrounds. Additionally, many deep learning object detection algorithms require substantial computational ...

Accurately predicting city-wide, short-term micromobility (MM) demand, particularly for docked bike-sharing systems, is essential for optimizing urban transportation networks and promoting sustainable mobility. The integration of multimodal data, ...

A lightweight seedling detection model with improved YOLOv8s is proposed to address the seedling identification problem in the replenishment process in industrial vegetable seedling production.The CBS module for feature extraction in Backbone and ...

The recommendation of passenger pickup zones can enhance driver efficiency, improve passenger experience, and optimize urban traffic management. However, current issues such as direct access to sensitive data and lack of data sharing between ...

Nowadays, people can write about their opinions of a product or service on social networks. These texts may contain information about a person’s likes or dislikes. Extracting sentiments or polarity from text is an important task to improve the ...

Despite the advancements in neural network technologies driving interactive image segmentation forward, challenges persist, especially concerning segmentation ambiguities caused by overlapping or visually similar objects against complex ...

Facial Expression Recognition (FER) has been a major development in a number of sectors in recent years. To reduce the problems caused by numerous parameters and high computational resource requirements of the current FER model, we propose a ...

Unmanned Aerial Vehicle (UAV) object detection plays a pivotal role in various fields such as civilian, business, and defense, but it faces obstacles such as different target dimensions, a preponderance of smaller targets, and complex environments ...

Recovering multi-person 3D poses from a single image is challenging due to depth ambiguity. Existing bottom-up methods show potential in resolving this by leveraging global contextual cues but suffer from unrelated information at two levels. At ...${}_{}$${}_{}$

The intrinsic similarity between camouflaged objects and background environment makes camouflaged object detection (COD) task more challenging than traditional object detection task. Since the boundary of the camouflage object is difficult to ...

With the success of Transformers, hybrid Transformer and CNN methods gain considerable popularity in medical image segmentation. These methods utilize a hybrid architecture that combines Transformers and CNNs to fuse global and local information, ...

Image deblurring has received significant progress due to the use of deep residual learning as it can help network training and model high-frequency information that is vital for image restoration. However, the blur does not only smooth the ...

Existing networks for fusing infrared and visible images, whe-ther CNN-based or Transformer-based, struggle to effectively extract and utilize global and local features, leading to poor fusion performance and accuracy. To address this, we propose ...

Deep hiding involves embedding a secret image within a cover image so that the secret becomes imperceptible to ensure the security of steganography. However, in practical applications, accuracy loss is due to data conversion during encoding and ...

Sequential recommendation (SR) aims to model user preferences through their historical interaction data. In recent years, Transformer has been widely used for SR due to its strong capability of modeling long-term dependencies. However, recent ...

Event-based bionic camera asynchronously captures dynamic scenes with high temporal resolution and high dynamic range, offering potential for the integration of events and RGB under conditions of illumination degradation and fast motion. Existing ...