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Found 30 papers, 13 papers with code
Adaptive Wavelet Filters as Practical Texture Feature Amplifiers for Parkinson's Disease Screening in OCT
Motivated by the above analysis, we propose a novel Adaptive Wavelet Filter (AWF) that serves as the Practical Texture Feature Amplifier to fully leverage the merits of texture features to boost the PD screening performance of DNNs with the aid of frequency domain learning.
Iterative Optimal Attention and Local Model for Single Image Rain Streak Removal
To address these limitations, we propose an Expectation Maximization Reconstruction Transformer (EMResformer) for single image rain streak removal.
RAD: Training an End-to-End Driving Policy via Large-Scale 3DGS-based Reinforcement Learning
By leveraging 3DGS techniques, we construct a photorealistic digital replica of the real physical world, enabling the AD policy to extensively explore the state space and learn to handle out-of-distribution scenarios through large-scale trial and error.
HedgeAgents: A Balanced-aware Multi-agent Financial Trading System
As automated trading gains traction in the financial market, algorithmic investment strategies are increasingly prominent.
MedFILIP: Medical Fine-grained Language-Image Pre-training
2) A knowledge injector is proposed to construct relationships between categories and visual attributes, which help the model to make judgments based on image features, and fosters knowledge extrapolation to unfamiliar disease categories.
Downlink Performance of Cell-Free Massive MIMO for LEO Satellite Mega-Constellation
Low-earth orbit (LEO) satellite communication (SatCom) has emerged as a promising technology for improving wireless connectivity in global areas.
Coverage and Spectral Efficiency of NOMA-Enabled LEO Satellite Networks with Ordering Schemes
Furthermore, for most SINR thresholds, the sum SE increases with the number of UTs to the highest value, whilst the maximum sum SE is obtained when there are two UTs.
Spectrum Sharing in Satellite-Terrestrial Integrated Networks: Frameworks, Approaches, and Opportunities
Furthermore, advanced SS approaches related to interference management in STINs and performance metrics of SS in STINs are introduced.
Benchmarking and Understanding Compositional Relational Reasoning of LLMs
Compositional relational reasoning (CRR) is a hallmark of human intelligence, but we lack a clear understanding of whether and how existing transformer large language models (LLMs) can solve CRR tasks.
ChainStream: An LLM-based Framework for Unified Synthetic Sensing
Many applications demand context sensing to offer personalized and timely services.
DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving
However, the numerous denoising steps in the robotic diffusion policy and the more dynamic, open-world nature of traffic scenes pose substantial challenges for generating diverse driving actions at a real-time speed.
Advancing Multi-Connectivity in Satellite-Terrestrial Integrated Networks: Architectures, Challenges, and Applications
Multi-connectivity (MC) in satellite-terrestrial integrated networks (STINs), included in the Third-Generation Partnership Project (3GPP) standards, is regarded as a promising technology for future networks, especially the non-terrestrial network (NTN).
A Bistatic Sensing System in Space-Air-Ground Integrated Networks
Sensing is anticipated to have wider extensions in communication systems with the boom of non-terrestrial networks (NTNs) during the past years.
RU22Fact: Optimizing Evidence for Multilingual Explainable Fact-Checking on Russia-Ukraine Conflict
Furthermore, we construct RU22Fact, a novel multilingual explainable fact-checking dataset on the Russia-Ukraine conflict in 2022 of 16K samples, each containing real-world claims, optimized evidence, and referenced explanation.
FinReport: Explainable Stock Earnings Forecasting via News Factor Analyzing Model
However, compared with financial institutions, it is not easy for ordinary investors to mine factors and analyze news.
Ranked #1 on
Stock Market Prediction
on Astock
Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security
Next, we discuss several key challenges to achieve intelligent, efficient and secure Personal LLM Agents, followed by a comprehensive survey of representative solutions to address these challenges.
An Analytical Model for Coordinated Multi-Satellite Joint Transmission System
In this paper, we investigate a coordinated multi-satellite joint transmission system from a system-level perspective, where a user can be served by multiple satellites to improve its quality-of-service (QoS).
AIGC In China: Current Developments And Future Outlook
The increasing attention given to AI Generated Content (AIGC) has brought a profound impact on various aspects of daily life, industrial manufacturing, and the academic sector.
Precheck Sequence Based False Base Station Detection During Handover: A Physical Layer Security Scheme
The source BS compares the uploaded signal power and shifts UE to another BS that can provide the strongest signal.
Sensing-Aided Peer-to-Peer Millimeter-Wave Communication
One of the bottlenecks of modern communications is to enable sensing and mutual communication simultaneously without causing scheduling conflicts, and how sensing may be leveraged to help directional communication accuracy.
Efficient automatic segmentation for multi-level pulmonary arteries: The PARSE challenge
Efficient automatic segmentation of multi-level (i. e. main and branch) pulmonary arteries (PA) in CTPA images plays a significant role in clinical applications.
The state-of-the-art 3D anisotropic intracranial hemorrhage segmentation on non-contrast head CT: The INSTANCE challenge
It is intended to resolve the above-mentioned problems and promote the development of both intracranial hemorrhage segmentation and anisotropic data processing.
STAR: SQL Guided Pre-Training for Context-dependent Text-to-SQL Parsing
Concretely, we propose two novel pre-training objectives which respectively explore the context-dependent interactions of NL utterances and SQL queries within each text-to-SQL conversation: (i) schema state tracking (SST) objective that tracks and explores the schema states of context-dependent SQL queries in the form of schema-states by predicting and updating the value of each schema slot during interaction; (ii) utterance dependency tracking (UDT) objective that employs weighted contrastive learning to pull together two semantically similar NL utterances and push away the representations of semantically dissimilar NL utterances within each conversation.
Siamese Contrastive Embedding Network for Compositional Zero-Shot Learning
Some methods recognize state and object with two trained classifiers, ignoring the impact of the interaction between object and state; the other methods try to learn the joint representation of the state-object compositions, leading to the domain gap between seen and unseen composition sets.
ULTRA: Uncertainty-aware Label Distribution Learning for Breast Tumor Cellularity Assessment
Therefore, automatic TC estimation is significant in clinical practice.
DISP6D: Disentangled Implicit Shape and Pose Learning for Scalable 6D Pose Estimation
Scalable 6D pose estimation for rigid objects from RGB images aims at handling multiple objects and generalizing to novel objects.
Trear: Transformer-based RGB-D Egocentric Action Recognition
In this paper, we propose a \textbf{Tr}ansformer-based RGB-D \textbf{e}gocentric \textbf{a}ction \textbf{r}ecognition framework, called Trear.
Transformer Guided Geometry Model for Flow-Based Unsupervised Visual Odometry
In this paper, we propose a method consisting of two camera pose estimators that deal with the information from pairwise images and a short sequence of images respectively.
Iterative Spectral Method for Alternative Clustering
Given a dataset and an existing clustering as input, alternative clustering aims to find an alternative partition.
Multi-step Cascaded Networks for Brain Tumor Segmentation
Automatic brain tumor segmentation method plays an extremely important role in the whole process of brain tumor diagnosis and treatment.
