-
Article
Multi-feature self-attention super-resolution network
In recent years, single-image super-resolution (SISR) methods based on the attention mechanism have been widely explored and achieved remarkable performances. However, most existing networks only explore chann...
-
Article
SSNet: a joint learning network for semantic segmentation and disparity estimation
Joint learning for semantic segmentation and disparity estimation is adopted to scene parsing for mutual benefit. However, existing joint learning approaches unify the two task briefly which may result in nega...
-
Chapter and Conference Paper
A Reference Vector Guided Evolutionary Algorithm with Diversity and Convergence Enhancement Strategies for Many-Objective Optimization
Maintaining the balance between convergence and diversity is a key issue in evolutionary multi-objective optimization and a challenge in many-objective scenarios. Reference-vector-guided selection is an exempl...
-
Chapter and Conference Paper
Edible Oil Price Forecasting: A Novel Approach with Group Temporal Convolutional Network and BetaAdaptiveAdam
Edible oil, a fundamental food commodity, plays a pivotal role in the economic progression of a nation. The precise forecasting of edible oil prices is of utmost significance to a broad spectrum of stakeholder...
-
Article
Spatial attention-guided deformable fusion network for salient object detection
Most of salient object detection methods employ U-shape architecture as the understructure. Although promising performance has been achieved, they struggle to detect salient objects with non-rigid shapes and a...
-
Chapter and Conference Paper
A Spatial-Temporal Deformable Attention Based Framework for Breast Lesion Detection in Videos
Detecting breast lesion in videos is crucial for computer-aided diagnosis. Existing video-based breast lesion detection approaches typically perform temporal feature aggregation of deep backbone features based...
-
Chapter and Conference Paper
Illumination-Guided Transformer-Based Network for Multispectral Pedestrian Detection
Multi-modal information (e.g., visible and thermal) can generate reliable and robust pedestrian detection results in various computer vision applications. Despite its broad applications, it remains a crucial p...
-
Chapter and Conference Paper
Video Instance Segmentation via Multi-Scale Spatio-Temporal Split Attention Transformer
State-of-the-art transformer-based video instance segmentation (VIS) approaches typically utilize either single-scale spatio-temporal features or per-frame multi-scale features during the attention computation...
-
Chapter and Conference Paper
An MOEA/D-ACO Algorithm with Finite Pheromone Weights for Bi-objective TTP
The Travelling Thief Problem is a complex logistics planning problem composed of the Travelling Salesman Problem and the Knapsack Problem. The Bi-objective TTP needs to optimize the two goals of the time spent...
-
Chapter and Conference Paper
SipMask: Spatial Information Preservation for Fast Image and Video Instance Segmentation
Single-stage instance segmentation approaches have recently gained popularity due to their speed and simplicity, but are still lagging behind in accuracy, compared to two-stage methods. We propose a fast singl...
-
Chapter
Deep Learning in Object Detection
Object detection is an important research area in image processing and computer vision. The performance of object detection has significantly improved through applying deep learning technology. Among these met...
