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Found 23 papers, 6 papers with code
Bridging Text and Molecule: A Survey on Multimodal Frameworks for Molecule
In this paper, we present the first systematic survey on multimodal frameworks for molecules research.
Weaver: Foundation Models for Creative Writing
Weaver is pre-trained on a carefully selected corpus that focuses on improving the writing capabilities of large language models.
Deep Blind Super-Resolution for Satellite Video
Therefore, this paper proposes a practical Blind SVSR algorithm (BSVSR) to explore more sharp cues by considering the pixel-wise blur levels in a coarse-to-fine manner.
Towards an end-to-end artificial intelligence driven global weather forecasting system
Initial states are typically generated by traditional data assimilation components, which are computational expensive and time-consuming.
FengWu-4DVar: Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation
Weather forecasting is a crucial yet highly challenging task.
EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution
Recently, convolutional networks have achieved remarkable development in remote sensing image Super-Resoltuion (SR) by minimizing the regression objectives, e. g., MSE loss.
"Reading Between the Heat": Co-Teaching Body Thermal Signatures for Non-intrusive Stress Detection
Stress impacts our physical and mental health as well as our social life.
LARA: A Light and Anti-overfitting Retraining Approach for Unsupervised Time Series Anomaly Detection
Retraining a large neural network model with limited data is vulnerable to overfitting.
Classifying Rhoticity of /r/ in Speech Sound Disorder using Age-and-Sex Normalized Formants
Mispronunciation detection tools could increase treatment access for speech sound disorders impacting, e. g., /r/.
Inferring High-level Geographical Concepts via Knowledge Graph and Multi-scale Data Integration: A Case Study of C-shaped Building Pattern Recognition
To improve efficiency and effectiveness, we integrate multi-scale data using a knowledge graph, focusing on the recognition of C-shaped building patterns.
Local-Global Temporal Difference Learning for Satellite Video Super-Resolution
To explore the global dependency in the entire frame sequence, a Long-term Temporal Difference Module (L-TDM) is proposed, where the differences between forward and backward segments are incorporated and activated to guide the modulation of the temporal feature, leading to a holistic global compensation.
Scaling Vision-based End-to-End Driving with Multi-View Attention Learning
We propose to replace CILRS with CIL++ as a strong vision-based pure end-to-end driving baseline supervised by only vehicle signals and trained by conditional imitation learning.
VeriCompress: A Tool to Streamline the Synthesis of Verified Robust Compressed Neural Networks from Scratch
This study introduces VeriCompress, a tool that automates the search and training of compressed models with robustness guarantees.
Privacy against Real-Time Speech Emotion Detection via Acoustic Adversarial Evasion of Machine Learning
Smart speaker voice assistants (VAs) such as Amazon Echo and Google Home have been widely adopted due to their seamless integration with smart home devices and the Internet of Things (IoT) technologies.
Psychophysiological Arousal in Young Children Who Stutter: An Interpretable AI Approach
We collected physiological parameters data from 70 children in the two target conditions.
Rib Suppression in Digital Chest Tomosynthesis
Digital chest tomosynthesis (DCT) is a technique to produce sectional 3D images of a human chest for pulmonary disease screening, with 2D X-ray projections taken within an extremely limited range of angles.
Action-Based Representation Learning for Autonomous Driving
Human drivers produce a vast amount of data which could, in principle, be used to improve autonomous driving systems.
On Learning Nominal Automata with Binders
This class of automata captures nominal regular languages; analogously to the classical language theory, nominal automata have been shown to characterise nominal regular expressions with binders.
Multimodal End-to-End Autonomous Driving
On the other hand, we find end-to-end driving approaches that try to learn a direct mapping from input raw sensor data to vehicle control signals.
Coherent Semantic Attention for Image Inpainting
The latest deep learning-based approaches have shown promising results for the challenging task of inpainting missing regions of an image.
Ranked #1 on
Image Inpainting
on Paris StreetView
Surrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data
We investigate the effectiveness of a simple solution to the common problem of deep learning in medical image analysis with limited quantities of labeled training data.
Interactive Deep Colorization With Simultaneous Global and Local Inputs
To solve this problem, we present a novel deep colorization method, which allows simultaneous global and local inputs to better control the output colorized images.
Joint convolutional neural pyramid for depth map super-resolution
The convolutional neural pyramids extract information from large receptive fields of the depth map and guidance map, while the convolutional neural network effectively transfers useful structures of the guidance image to the depth image.
