Search Results for author:
Found 23 papers, 13 papers with code
Anomaly Detection in Electrocardiograms: Advancing Clinical Diagnosis Through Self-Supervised Learning
We introduce a novel self-supervised learning framework for ECG AD, utilizing a vast dataset of normal ECGs to autonomously detect and localize cardiac anomalies.
Self-Supervised Anomaly Detection
Self-Supervised Learning
+2
SpikeReveal: Unlocking Temporal Sequences from Real Blurry Inputs with Spike Streams
Our approach begins with the formulation of a spike-guided deblurring model that explores the theoretical relationships among spike streams, blurry images, and their corresponding sharp sequences.
Can Deception Detection Go Deeper? Dataset, Evaluation, and Benchmark for Deception Reasoning
To address data scarcity, this paper proposes a new data collection pipeline.
Global Tropical Cyclone Intensity Forecasting with Multi-modal Multi-scale Causal Autoregressive Model
Accurate forecasting of Tropical cyclone (TC) intensity is crucial for formulating disaster risk reduction strategies.
ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast
Data-driven weather forecast based on machine learning (ML) has experienced rapid development and demonstrated superior performance in the global medium-range forecast compared to traditional physics-based dynamical models.
FengWu-GHR: Learning the Kilometer-scale Medium-range Global Weather Forecasting
Therefore, building a kilometer-scale global forecast model is a persistent pursuit in the meteorology domain.
Efficient Image Deblurring Networks based on Diffusion Models
This article introduces a sliding window model for defocus deblurring that achieves the best performance to date with extremely low memory usage.
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.
Textual Prompt Guided Image Restoration
In this paper, an effective textual prompt guided image restoration model has been proposed.
GPT-4V with Emotion: A Zero-shot Benchmark for Generalized Emotion Recognition
To bridge this gap, we present the quantitative evaluation results of GPT-4V on 21 benchmark datasets covering 6 tasks: visual sentiment analysis, tweet sentiment analysis, micro-expression recognition, facial emotion recognition, dynamic facial emotion recognition, and multimodal emotion recognition.
Multi-scale Cross-restoration Framework for Electrocardiogram Anomaly Detection
To address this challenge, this paper introduces a novel multi-scale cross-restoration framework for ECG anomaly detection and localization that considers both local and global ECG characteristics.
MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learning
The first Multimodal Emotion Recognition Challenge (MER 2023) was successfully held at ACM Multimedia.
FengWu: Pushing the Skillful Global Medium-range Weather Forecast beyond 10 Days Lead
We present FengWu, an advanced data-driven global medium-range weather forecast system based on Artificial Intelligence (AI).
VTQA: Visual Text Question Answering via Entity Alignment and Cross-Media Reasoning
The ideal form of Visual Question Answering requires understanding, grounding and reasoning in the joint space of vision and language and serves as a proxy for the AI task of scene understanding.
Learning Analytical Posterior Probability for Human Mesh Recovery
Despite various probabilistic methods for modeling the uncertainty and ambiguity in human mesh recovery, their overall precision is limited because existing formulations for joint rotations are either not constrained to SO(3) or difficult to learn for neural networks.
CLIPVG: Text-Guided Image Manipulation Using Differentiable Vector Graphics
Considerable progress has recently been made in leveraging CLIP (Contrastive Language-Image Pre-Training) models for text-guided image manipulation.
TODE-Trans: Transparent Object Depth Estimation with Transformer
We observe that the global characteristics of the transformer make it easier to extract contextual information to perform depth estimation of transparent areas.
Multi-Forgery Detection Challenge 2022: Push the Frontier of Unconstrained and Diverse Forgery Detection
In this paper, we present the solutions from the Top 3 teams, in order to boost the research work in the field of image forgery detection.
LookinGood^π: Real-time Person-independent Neural Re-rendering for High-quality Human Performance Capture
The guidance of the rendered image is realized by blending features from two branches effectively in the training of the detail branch, which improves both the warping accuracy and the details' fidelity.
Occlum: Secure and Efficient Multitasking Inside a Single Enclave of Intel SGX
SFI is a software instrumentation technique for sandboxing untrusted modules (called domains).
Operating Systems Hardware Architecture Cryptography and Security
Robust Invisible Hyperlinks in Physical Photographs Based on 3D Rendering Attacks
To train a robust decoder against the physical distortion from the real world, a distortion network based on 3D rendering is inserted between the encoder and the decoder to simulate the camera imaging process.
Long Short-Term Attention
Attention is an important cognition process of humans, which helps humans concentrate on critical information during their perception and learning.
