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Found 11 papers, 4 papers with code
CLAD: Robust Audio Deepfake Detection Against Manipulation Attacks with Contrastive Learning
The detection models exhibited vulnerabilities, with FAR rising to 36. 69%, 31. 23%, and 51. 28% under volume control, fading, and noise injection, respectively.
Harnessing Joint Rain-/Detail-aware Representations to Eliminate Intricate Rains
By integrating CoI-M with the rain-/detail-aware Contrastive learning, we develop CoIC, an innovative and potent algorithm tailored for training models on mixed datasets.
Focus On Details: Online Multi-object Tracking with Diverse Fine-grained Representation
This fine-grained representation requires high feature resolution and precise semantic information.
Spatial-temporal associations representation and application for process monitoring using graph convolution neural network
Thank you very much for the attention and concern of colleagues and scholars in this work.
A Verification Framework for Certifying Learning-Based Safety-Critical Aviation Systems
We present a safety verification framework for design-time and run-time assurance of learning-based components in aviation systems.
A Framework for Multi-stage Bonus Allocation in meal delivery Platform
The semi-black-box acceptance probability model is employed to forecast the relationship between the bonus allocated to order and its acceptance probability, the Lagrangian dual-based dynamic programming algorithm aims to calculate the empirical Lagrangian multiplier for each allocation stage offline based on the historical data set, and the online allocation algorithm uses the results attained in the offline part to calculate a proper delivery bonus for each order.
MMLN: Leveraging Domain Knowledge for Multimodal Diagnosis
Recent studies show that deep learning models achieve good performance on medical imaging tasks such as diagnosis prediction.
ACNet: Approaching-and-Centralizing Network for Zero-Shot Sketch-Based Image Retrieval
The huge domain gap between sketches and photos and the highly abstract sketch representations pose challenges for sketch-based image retrieval (\underline{SBIR}).
Using Quantifier Elimination to Enhance the Safety Assurance of Deep Neural Networks
Advances in the field of Machine Learning and Deep Neural Networks (DNNs) has enabled rapid development of sophisticated and autonomous systems.
Evaluating Generalization Ability of Convolutional Neural Networks and Capsule Networks for Image Classification via Top-2 Classification
In this paper, we propose a new image classification task called Top-2 classification to evaluate the generalization ability of CNNs and CapsNets.
Compositional Coding Capsule Network with K-Means Routing for Text Classification
Combined with our compositional weighted coding method and the routing algorithm, we design a neural network for text classification.
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