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Found 16 papers, 6 papers with code
Occlusion-Aware Siamese Network for Human Pose Estimation
To overcome the defects caused by the erasing operation, we perform feature reconstruction to recover the information destroyed by occlusion and details lost in cleaning procedure.
Mechanism of Electricacupuncture Treating Detrusor Bladder Neck Dyscoordination After Suprasacral Spinal Cord Injury by Proteomics
On day 29 post-injury, all rats underwent urodynamic assessments, followed by hematoxylin and eosin (HE) staining, tandem mass tag (TMT) proteomics, and Western blot (WB) analysis of the detrusor and bladder neck tissues.
Improving Integrated Gradient-based Transferable Adversarial Examples by Refining the Integration Path
We propose the Multiple Monotonic Diversified Integrated Gradients (MuMoDIG) attack, which can generate highly transferable adversarial examples on different CNN and ViT models and defenses.
Adversarial Attacks of Vision Tasks in the Past 10 Years: A Survey
Adversarial attacks, which manipulate input data to undermine model availability and integrity, pose significant security threats during machine learning inference.
The KnowWhereGraph Ontology
KnowWhereGraph is one of the largest fully publicly available geospatial knowledge graphs.
Study of the mechanism of electroacupuncture regulating ferroptosis, inhibiting bladder neck fibrosis, and improving bladder urination function after suprasacral spinal cord injury using proteomics
Purpose The aim of this study was to explore whether electroacupuncture regulates phenotypic transformation of smooth muscle cells by inhibiting ferroptosis and inhibiting fibrosis, thereby improving bladder urination function after suprasacral spinal cord injury (SSCI).
SSL-OTA: Unveiling Backdoor Threats in Self-Supervised Learning for Object Detection
The extensive adoption of Self-supervised learning(SSL) has led to an increased security threat from backdoor attacks.
Sparse Federated Training of Object Detection in the Internet of Vehicles
However, the current object detection methods are mostly based on centralized deep training, that is, the sensitive data obtained by edge devices need to be uploaded to the server, which raises privacy concerns.
Temporal-Channel Topology Enhanced Network for Skeleton-Based Action Recognition
Most current methods adopt graph convolutional network (GCN) for topology modeling, but GCN-based methods are limited in long-distance correlation modeling and generalizability.
Auto-weighted Multi-view Clustering for Large-scale Data
Multi-view clustering has gained broad attention owing to its capacity to exploit complementary information across multiple data views.
ESKNet-An enhanced adaptive selection kernel convolution for breast tumors segmentation
Breast cancer is one of the common cancers that endanger the health of women globally.
PromptAttack: Prompt-based Attack for Language Models via Gradient Search
Therefore, in this paper, we propose a malicious prompt template construction method (\textbf{PromptAttack}) to probe the security performance of PLMs.
Ontology Design Facilitating Wikibase Integration -- and a Worked Example for Historical Data
Wikibase -- which is the software underlying Wikidata -- is a powerful platform for knowledge graph creation and management.
Combating Distribution Shift for Accurate Time Series Forecasting via Hypernetworks
In this paper, we propose Hyper Time- Series Forecasting (HTSF), a hypernetwork-based framework for accurate time series forecasting under distribution shift.
Neuro-Symbolic Artificial Intelligence: Current Trends
Neuro-Symbolic Artificial Intelligence -- the combination of symbolic methods with methods that are based on artificial neural networks -- has a long-standing history.
Completion Reasoning Emulation for the Description Logic EL+
We present a new approach to integrating deep learning with knowledge-based systems that we believe shows promise.
