2.2k citations · 3.2k across the 37 of their papers we have counts for
40 papers
EOS-Bench: A Comprehensive Benchmark for Earth Observation Satellite Scheduling
Qian Yin, Jiaxing Li, Jiaqi Cheng +23
Earth observation satellite imaging scheduling is a challenging NP-hard combinatorial optimisation problem central to space mission operations. While next-generation agile Earth ob…
An adaptive experience-based discrete genetic algorithm for multi-trip picking robot task scheduling in smart orchards
Peng Chen, Jing Liangb, Kang-Jia Qiao +5
The continuous innovation of smart robotic technologies is driving the development of smart orchards, significantly enhancing the potential for automated harvesting systems. While…
A segment anchoring-based balancing algorithm for agricultural multi-robot task allocation with energy constraints
Peng Chen, Jing Liang, Kang-Jia Qiao +6
Multi-robot systems have emerged as a key technology for addressing the efficiency and cost challenges in labor-intensive industries. In the representative scenario of smart farmin…
RoadSens-4M: A Multimodal Smartphone & Camera Dataset for Holistic Road-way Analysis
Amith Khandakar, David Michelson, Shaikh Golam Rabbani +8
It's important to monitor road issues such as bumps and potholes to enhance safety and improve road conditions. Smartphones are equipped with various built-in sensors that offer a…
Randomized Neural Network with Adaptive Forward Regularization for Online Task-free Class Incremental Learning
Junda Wang, Minghui Hu, Ning Li +2
Class incremental learning (CIL) requires an agent to learn distinct tasks consecutively with knowledge retention against forgetting. Problems impeding the practical applications o…
Multi-Scale Finetuning for Encoder-based Time Series Foundation Models
Zhongzheng Qiao, Chenghao Liu, Yiming Zhang +6
Time series foundation models (TSFMs) demonstrate impressive zero-shot performance for time series forecasting. However, an important yet underexplored challenge is how to effectiv…
R^2VFL: A Robust Random Vector Functional Link Network with Huber-Weighted Framework
Anuradha Kumari, Mushir Akhtar, P. N. Suganthan +1
The random vector functional link (RVFL) neural network has shown significant potential in overcoming the constraints of traditional artificial neural networks, such as excessive c…
Learning Strategies in Particle Swarm Optimizer: A Critical Review and Performance Analysis
Dikshit Chauhan, Shivani, P. N. Suganthan
Nature has long inspired the development of swarm intelligence (SI), a key branch of artificial intelligence that models collective behaviors observed in biological systems for sol…
Incremental Online Learning of Randomized Neural Network with Forward Regularization
Junda Wang, Minghui Hu, Ning Li +2
Online learning of deep neural networks suffers from challenges such as hysteretic non-incremental updating, increasing memory usage, past retrospective retraining, and catastrophi…
Adaptive Hierarchical Graph Cut for Multi-granularity Out-of-distribution Detection
Xiang Fang, Arvind Easwaran, Blaise Genest +1
This paper focuses on a significant yet challenging task: out-of-distribution detection (OOD detection), which aims to distinguish and reject test samples with semantic shifts, so…
Your Data Is Not Perfect: Towards Cross-Domain Out-of-Distribution Detection in Class-Imbalanced Data
Xiang Fang, Arvind Easwaran, Blaise Genest +1
Previous OOD detection systems only focus on the semantic gap between ID and OOD samples. Besides the semantic gap, we are faced with two additional gaps: the domain gap between so…
A Tutorial on the Design, Experimentation and Application of Metaheuristic Algorithms to Real-World Optimization Problems
Eneko Osaba, Esther Villar-Rodriguez, Javier Del Ser +6
In the last few years, the formulation of real-world optimization problems and their efficient solution via metaheuristic algorithms has been a catalyst for a myriad of research st…
Vanilla Gradient Descent for Oblique Decision Trees
Subrat Prasad Panda, Blaise Genest, Arvind Easwaran +1
Decision Trees (DTs) constitute one of the major highly non-linear AI models, valued, e.g., for their efficiency on tabular data. Learning accurate DTs is, however, complicated, es…
Underwater Acoustic Signal Denoising Algorithms: A Survey of the State-of-the-art
Ruobin Gao, Maohan Liang, Heng Dong +2
This paper comprehensively reviews recent advances in underwater acoustic signal denoising, an area critical for improving the reliability and clarity of underwater communication a…
Ensemble Deep Random Vector Functional Link Neural Network Based on Fuzzy Inference System
M. Sajid, M. Tanveer, P. N. Suganthan
The ensemble deep random vector functional link (edRVFL) neural network has demonstrated the ability to address the limitations of conventional artificial neural networks. However,…
A Two-stage Evolutionary Framework For Multi-objective Optimization
Peng Chen, Jing Liang, Kangjia Qiao +2
In the field of evolutionary multi-objective optimization, the approximation of the Pareto front (PF) is achieved by utilizing a collection of representative candidate solutions th…
Versatile LiDAR-Inertial Odometry With SE (2) Constraints for Ground Vehicles
Jiaying Chen, Han Wang, Minghui Hu +1
LiDAR SLAM has become one of the major localization systems for ground vehicles since LiDAR Odometry And Mapping (LOAM). Many extension works on LOAM mainly leverage one specific c…
Class-incremental Learning for Time Series: Benchmark and Evaluation
Zhongzheng Qiao, Quang Pham, Zhen Cao +4
Real-world environments are inherently non-stationary, frequently introducing new classes over time. This is especially common in time series classification, such as the emergence…
IF2Net: Innately Forgetting-Free Networks for Continual Learning
Depeng Li, Tianqi Wang, Bingrong Xu +3
Continual learning can incrementally absorb new concepts without interfering with previously learned knowledge. Motivated by the characteristics of neural networks, in which inform…
Heterogeneous Oblique Double Random Forest
M. A. Ganaie, M. Tanveer, I. Beheshti +2
The decision tree ensembles use a single data feature at each node for splitting the data. However, splitting in this manner may fail to capture the geometric properties of the dat…
A Reinforcement Learning-assisted Genetic Programming Algorithm for Team Formation Problem Considering Person-Job Matching
Yangyang Guo, Hao Wang, Lei He +3
An efficient team is essential for the company to successfully complete new projects. To solve the team formation problem considering person-job matching (TFP-PJM), a 0-1 integer p…
SFE: A Simple, Fast and Efficient Feature Selection Algorithm for High-Dimensional Data
Behrouz Ahadzadeh, Moloud Abdar, Fatemeh Safara +3
In this paper, a new feature selection algorithm, called SFE (Simple, Fast, and Efficient), is proposed for high-dimensional datasets. The SFE algorithm performs its search process…
anafi_ros: from Off-the-Shelf Drones to Research Platforms
Andriy Sarabakha
The off-the-shelf drones are simple to operate and easy to maintain aerial systems. However, due to proprietary flight software, these drones usually do not provide any open-source…
Ensemble Reinforcement Learning: A Survey
Yanjie Song, P. N. Suganthan, Witold Pedrycz +4
Reinforcement Learning (RL) has emerged as a highly effective technique for addressing various scientific and applied problems. Despite its success, certain complex tasks remain ch…