Search Results for author:
Found 13 papers, 8 papers with code
Human-machine cooperation: optimization of drug retrieval sequencing in automated drug dispensing systems
Through experimental comparisons of average picking times for prescription orders under various operational conditions, we demonstrate that a system layout design incorporating two input/output points significantly enhances the efficiency of prescription order fulfilment within a human-machine cooperation environment.
FP8-LM: Training FP8 Large Language Models
In this paper, we explore FP8 low-bit data formats for efficient training of large language models (LLMs).
TinyCLIP: CLIP Distillation via Affinity Mimicking and Weight Inheritance
In this paper, we propose a novel cross-modal distillation method, called TinyCLIP, for large-scale language-image pre-trained models.
Driving Style Recognition at First Impression for Online Trajectory Prediction
This paper proposes a new driving style recognition approach that allows autonomous vehicles (AVs) to perform trajectory predictions for surrounding vehicles with minimal data.
CBLab: Supporting the Training of Large-scale Traffic Control Policies with Scalable Traffic Simulation
To the best of our knowledge, CBLab is the first infrastructure supporting traffic control policy optimization in large-scale urban scenarios.
TinyViT: Fast Pretraining Distillation for Small Vision Transformers
It achieves a top-1 accuracy of 84. 8% on ImageNet-1k with only 21M parameters, being comparable to Swin-B pretrained on ImageNet-21k while using 4. 2 times fewer parameters.
Ranked #135 on
Image Classification
on ImageNet
MiniViT: Compressing Vision Transformers with Weight Multiplexing
The central idea of MiniViT is to multiplex the weights of consecutive transformer blocks.
Ranked #212 on
Image Classification
on ImageNet
(using extra training data)
Searching the Search Space of Vision Transformer
Vision Transformer has shown great visual representation power in substantial vision tasks such as recognition and detection, and thus been attracting fast-growing efforts on manually designing more effective architectures.
Rethinking and Improving Relative Position Encoding for Vision Transformer
We then propose new relative position encoding methods dedicated to 2D images, called image RPE (iRPE).
Ranked #140 on
Object Detection
on COCO minival
LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search
Object tracking has achieved significant progress over the past few years.
Harvesting Visual Objects from Internet Images via Deep Learning Based Objectness Assessment
As a concrete example, a database of over 1. 2 million visual objects has been built using the proposed method, and has been successfully used in various data-driven image applications.
Tumour Ellipsification in Ultrasound Images for Treatment Prediction in Breast Cancer
One of the earliest steps in using QUS methods is contouring a region of interest (ROI) inside the tumour in ultrasound B-mode images.
Weakly Learning to Match Experts in Online Community
The challenge is how to trade off the matching degree between users' expertise and the question topic, and the likelihood of positive response from the invited users.
