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Found 16 papers, 5 papers with code
ScaleMAI: Accelerating the Development of Trusted Datasets and AI Models
This process often delays AI benefits, as human-centric data creation and AI-centric model development are treated as separate, sequential steps.
mR$^2$AG: Multimodal Retrieval-Reflection-Augmented Generation for Knowledge-Based VQA
Thus, multimodal Retrieval-Augmented Generation (mRAG) is naturally introduced to provide MLLMs with comprehensive and up-to-date knowledge, effectively expanding the knowledge scope.
Automatic parking planning control method based on improved A* algorithm
To address the high real-time, high precision, and high trajectory quality requirements posed by the automatic parking task under real-time perceived local maps, this paper proposes an improved automatic parking planning algorithm based on the A* algorithm, and uses Model Predictive Control (MPC) as the control module for automatic parking. The algorithm enhances the planning real-time performance by optimizing heuristic functions, binary heap optimization, and bidirectional search; it calculates the passability of narrow areas by dynamically loading obstacles and introduces the vehicle's own volume during planning; it improves trajectory quality by using neighborhood expansion and Bezier curve optimization methods to meet the high trajectory quality requirements of the parking task.
Automated Parking Planning with Vision-Based BEV Approach
Automated Valet Parking (AVP) is a crucial component of advanced autonomous driving systems, focusing on the endpoint task within the "human-vehicle interaction" process to tackle the challenges of the "last mile". The perception module of the automated parking algorithm has evolved from local perception using ultrasonic radar and global scenario precise map matching for localization to a high-level map-free Birds Eye View (BEV) perception solution. The BEV scene places higher demands on the real-time performance and safety of automated parking planning tasks.
Brain-inspired and Self-based Artificial Intelligence
In this paper, we introduce a Brain-inspired and Self-based Artificial Intelligence (BriSe AI) paradigm.
Lens-to-lens bokeh effect transformation. NTIRE 2023 challenge report
We present the new Bokeh Effect Transformation Dataset (BETD), and review the proposed solutions for this novel task at the NTIRE 2023 Bokeh Effect Transformation Challenge.
Brain-inspired bodily self-perception model for robot rubber hand illusion
Despite the conceptual descriptions of the mechanisms of bodily self-consciousness and the possible relevant brain areas, the existing theoretical models still lack an explanation of the computational mechanisms by which the brain encodes the perception of one's body and how our subjectively perceived body illusions can be generated by neural networks.
Optimal Sizing of Isolated Renewable Power Systems with Ammonia Synthesis: Model and Solution Approach
However, multi-timescale electricity, hydrogen, and ammonia storages, minimum power supply for system safety, and the multi-year uncertainty of renewable generation lead to difficulties in planning.
Optimal Sizing and Pricing of Renewable Power to Ammonia Systems Considering the Limited Flexibility of Ammonia Synthesis
This paper proposes an optimal sizing and pricing method for RePtA system planning.
A Comparative Study of Compartmental Models for COVID-19 Transmission in Ontario, Canada
The continued spread of the virus underlying COVID-19 has been spurred by the emergence of variants since the initial outbreak in December, 2019.
BrainCog: A Spiking Neural Network based Brain-inspired Cognitive Intelligence Engine for Brain-inspired AI and Brain Simulation
These brain-inspired AI models have been effectively validated on various supervised, unsupervised, and reinforcement learning tasks, and they can be used to enable AI models to be with multiple brain-inspired cognitive functions.
DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection
Few-shot object detection, which aims at detecting novel objects rapidly from extremely few annotated examples of previously unseen classes, has attracted significant research interest in the community.
Ranked #5 on
Few-Shot Object Detection
on MS-COCO (1-shot)
Online Missing Value Imputation and Change Point Detection with the Gaussian Copula
Missing value imputation is crucial for real-world data science workflows.
Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula
The time required to fit the model scales linearly with the number of rows and the number of columns in the dataset.
Multimodal Affective States Recognition Based on Multiscale CNNs and Biologically Inspired Decision Fusion Model
There has been an encouraging progress in the affective states recognition models based on the single-modality signals as electroencephalogram (EEG) signals or peripheral physiological signals in recent years.
