Search Results for author:
Found 14 papers, 1 papers with code
Expanding Event Modality Applications through a Robust CLIP-Based Encoder
While large-scale datasets have significantly advanced image-based models, the scarcity of comprehensive event datasets has limited performance potential in event modality.
VLTP: Vision-Language Guided Token Pruning for Task-Oriented Segmentation
We design a new pruning decoder to take both image tokens and vision-language guidance as input to predict the relevance of each image token to the task.
Promoting Fairness in Link Prediction with Graph Enhancement
Link prediction is a crucial task in network analysis, but it has been shown to be prone to biased predictions, particularly when links are unfairly predicted between nodes from different sensitive groups.
Recoverable Anonymization for Pose Estimation: A Privacy-Enhancing Approach
By jointly optimizing a privacy-enhancing module, a privacy recovery module, and a pose estimator, our system ensures robust privacy protection, efficient SPI recovery, and high-performance HPE.
Vision Language Model for Interpretable and Fine-grained Detection of Safety Compliance in Diverse Workplaces
Nonetheless, VLMs face challenges in consistently verifying PPE attributes due to the complexity and variability of workplace environments, requiring them to interpret context-specific language and visual cues simultaneously.
EcoSense: Energy-Efficient Intelligent Sensing for In-Shore Ship Detection through Edge-Cloud Collaboration
Detecting marine objects inshore presents challenges owing to algorithmic intricacies and complexities in system deployment.
TaskCLIP: Extend Large Vision-Language Model for Task Oriented Object Detection
Nevertheless, the naive application of VLMs leads to sub-optimal quality, due to the misalignment between embeddings of object images and their visual attributes, which are mainly adjective phrases.
HDReason: Algorithm-Hardware Codesign for Hyperdimensional Knowledge Graph Reasoning
When conducting cross-models and cross-platforms comparison, HDReason yields an average 4. 2x higher performance and 3. 4x better energy efficiency with similar accuracy versus the state-of-the-art FPGA-based GCN training platform.
HEAL: Brain-inspired Hyperdimensional Efficient Active Learning
Drawing inspiration from the outstanding learning capability of our human brains, Hyperdimensional Computing (HDC) emerges as a novel computing paradigm, and it leverages high-dimensional vector presentation and operations for brain-like lightweight Machine Learning (ML).
A Plug-in Tiny AI Module for Intelligent and Selective Sensor Data Transmission
To enhance the framework's performance, the training process is customized and a "lazy" sensor deactivation strategy utilizing temporal information is introduced.
HyperSense: Hyperdimensional Intelligent Sensing for Energy-Efficient Sparse Data Processing
Introducing HyperSense, our co-designed hardware and software system efficiently controls Analog-to-Digital Converter (ADC) modules' data generation rate based on object presence predictions in sensor data.
Towards Efficient Hyperdimensional Computing Using Photonics
Over the past few years, silicon photonics-based computing has emerged as a promising alternative to CMOS-based computing for Deep Neural Networks (DNN).
Ethosight: A Reasoning-Guided Iterative Learning System for Nuanced Perception based on Joint-Embedding & Contextual Label Affinity
Traditional computer vision models often necessitate extensive data acquisition, annotation, and validation.
Late Breaking Results: Scalable and Efficient Hyperdimensional Computing for Network Intrusion Detection
Cybersecurity has emerged as a critical challenge for the industry.
