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Found 18 papers, 2 papers with code
Struggle with Adversarial Defense? Try Diffusion
Unlike data-driven classifiers, TMDC, guided by Bayesian principles, utilizes the conditional likelihood from diffusion models to determine the class probabilities of input images, thereby insulating against the influences of data shift and the limitations of adversarial training.
URLBERT:A Contrastive and Adversarial Pre-trained Model for URL Classification
To address this gap, this paper introduces URLBERT, the first pre-trained representation learning model applied to a variety of URL classification or detection tasks.
Learning to Prompt Knowledge Transfer for Open-World Continual Learning
This paper studies the problem of continual learning in an open-world scenario, referred to as Open-world Continual Learning (OwCL).
Dynamic Frequency Domain Graph Convolutional Network for Traffic Forecasting
Complex spatial dependencies in transportation networks make traffic prediction extremely challenging.
3D Scene Creation and Rendering via Rough Meshes: A Lighting Transfer Avenue
However, a drawback is that the synthesized views through Neural Fields Rendering (NFR) cannot reflect the simulated lighting details on R3DMs in PBR pipelines, especially when object interactions in the 3D scene creation cause local shadows.
Gaze Estimation Approach Using Deep Differential Residual Network
We propose a differential residual model (DRNet) combined with a new loss function to make use of the difference information of two eye images.
Can autism be diagnosed with AI?
With AI, new radiomic models using the deep learning techniques will be also described.
Reason induced visual attention for explainable autonomous driving
Deep learning (DL) based computer vision (CV) models are generally considered as black boxes due to poor interpretability.
Semi-Supervised Auto-Encoder Graph Network for Diabetic Retinopathy Grading
We propose a Semi-supervised Auto-encoder Graph Network (SAGN) for the challenging DR diagnosis to relax this constraint.
Using UAVs for vehicle tracking and collision risk assessment at intersections
Assessing collision risk is a critical challenge to effective traffic safety management.
Confused Modulo Projection based Somewhat Homomorphic Encryption -- Cryptosystem, Library and Applications on Secure Smart Cities
To make this algorithm easy to use, we also designed and implemented an efficient general blind computing library based on CMP-SWHE.
A DRL-based Multiagent Cooperative Control Framework for CAV Networks: a Graphic Convolution Q Network
Connected Autonomous Vehicle (CAV) Network can be defined as a collection of CAVs operating at different locations on a multilane corridor, which provides a platform to facilitate the dissemination of operational information as well as control instructions.
Leveraging the Capabilities of Connected and Autonomous Vehicles and Multi-Agent Reinforcement Learning to Mitigate Highway Bottleneck Congestion
In addressing this objective, we duly recognize that one of the main challenges of RL-based CAV controllers is the variety and complexity of inputs that exist in the real world, such as the information provided to the CAV by other connected entities and sensed information.
Facilitating Connected Autonomous Vehicle Operations Using Space-weighted Information Fusion and Deep Reinforcement Learning Based Control
From a general perspective, its implementation can provide guidance to connectivity equipment manufacturers and CAV operators, regarding the default CR settings for CAVs or the recommended CR setting in a given traffic environment.
CONet: A Cognitive Ocean Network
The Cognitive Ocean Network (CONet) will become the mainstream of future ocean science and engineering developments.
Brain Intelligence: Go Beyond Artificial Intelligence
Specifically, we plan to develop an intelligent learning model called Brain Intelligence (BI) that generates new ideas about events without having experienced them by using artificial life with an imagine function.
Underwater Optical Image Processing: A Comprehensive Review
This paper aims to review the state-of-the-art techniques in underwater image processing by highlighting the contributions and challenges presented in over 40 papers.
Single Image Dehazing through Improved Atmospheric Light Estimation
Image contrast enhancement for outdoor vision is important for smart car auxiliary transport systems.
