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Found 10 papers, 3 papers with code
High-speed Low-consumption sEMG-based Transient-state micro-Gesture Recognition
The accuracy of the proposed SNN is 83. 85% and 93. 52% on the two datasets respectively.
Pink-Eggs Dataset V1: A Step Toward Invasive Species Management Using Deep Learning Embedded Solutions
We introduce a novel dataset consisting of images depicting pink eggs that have been identified as Pomacea canaliculata eggs, accompanied by corresponding bounding box annotations.
Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training
Vision transformers (ViTs) have recently obtained success in many applications, but their intensive computation and heavy memory usage at both training and inference time limit their generalization.
HeatViT: Hardware-Efficient Adaptive Token Pruning for Vision Transformers
While vision transformers (ViTs) have continuously achieved new milestones in the field of computer vision, their sophisticated network architectures with high computation and memory costs have impeded their deployment on resource-limited edge devices.
Data Level Lottery Ticket Hypothesis for Vision Transformers
That is, there exists a subset of input image patches such that a ViT can be trained from scratch by using only this subset of patches and achieve similar accuracy to the ViTs trained by using all image patches.
Transporters with Visual Foresight for Solving Unseen Rearrangement Tasks
We propose a visual foresight model for pick-and-place rearrangement manipulation which is able to learn efficiently.
SPViT: Enabling Faster Vision Transformers via Soft Token Pruning
Moreover, our framework can guarantee the identified model to meet resource specifications of mobile devices and FPGA, and even achieve the real-time execution of DeiT-T on mobile platforms.
Ranked #4 on
Efficient ViTs
on ImageNet-1K (with DeiT-S)
HFSP: A Hardware-friendly Soft Pruning Framework for Vision Transformers
Recently, Vision Transformer (ViT) has continuously established new milestones in the computer vision field, while the high computation and memory cost makes its propagation in industrial production difficult.
Put the Bear on the Chair! Intelligent Robot Interaction with Previously Unseen Chairs via Robot Imagination
Results show that our method enables the robot to autonomously seat the teddy bear on the 12 previously unseen chairs with a very high success rate.
Assessment of central serous chorioretinopathy (CSC) depicted on color fundus photographs using deep Learning
To investigate whether and to what extent central serous chorioretinopathy (CSC) depicted on color fundus photographs can be assessed using deep learning technology.
