no code implementations • 14 Feb 2024 • Yiming Bu, Jiayang Liu, Qinru Qiu
The Dynamic Vision Sensor (DVS) is an innovative technology that efficiently captures and encodes visual information in an event-driven manner.
1 code implementation • 23 Jan 2024 • Mingyang Li, Yue Ma, Qinru Qiu
This approach enables the creation of a semantic map of the environment and ensures reliable camera localization.
no code implementations • 17 Jan 2024 • Yinuo Zhao, Kun Wu, Tianjiao Yi, Zhiyuan Xu, Xiaozhu Ju, Zhengping Che, Qinru Qiu, Chi Harold Liu, Jian Tang
Visuomotor policies, which learn control mechanisms directly from high-dimensional visual observations, confront challenges in adapting to new environments with intricate visual variations.
no code implementations • 17 Jan 2024 • Kun Wu, Ning Liu, Zhen Zhao, Di Qiu, Jinming Li, Zhengping Che, Zhiyuan Xu, Qinru Qiu, Jian Tang
Imitation learning (IL), aiming to learn optimal control policies from expert demonstrations, has been an effective method for robot manipulation tasks.
no code implementations • 20 Dec 2023 • Chengxiang Yin, Zhengping Che, Kun Wu, Zhiyuan Xu, Qinru Qiu, Jian Tang
Video Question Answering (VideoQA) is a very attractive and challenging research direction aiming to understand complex semantics of heterogeneous data from two domains, i. e., the spatio-temporal video content and the word sequence in question.
no code implementations • 21 Jul 2023 • Zhenhang Zhang, Jingang Jin, Haowen Fang, Qinru Qiu
The algorithm not only learns the synaptic weight but also adapts the temporal filters associated to the synapses.
no code implementations • 8 May 2021 • Amar Shrestha, Haowen Fang, Daniel Patrick Rider, Zaidao Mei, Qinru Qiu
Although widely used in machine learning, backpropagation cannot directly be applied to SNN training and is not feasible on a neuromorphic processor that emulates biological neuron and synapses.
no code implementations • 21 Apr 2021 • Haowen Fang, Brady Taylor, Ziru Li, Zaidao Mei, Hai Li, Qinru Qiu
This circuit implementation of the neuron model is simulated to demonstrate its ability to react to temporal spiking patterns with an adaptive threshold.
no code implementations • 7 Jul 2020 • Haowen Fang, Amar Shrestha, Qinru Qiu
A training algorithm to classify spatial temporal patterns is also proposed.
no code implementations • 6 Jun 2020 • Amar Shrestha, Krittaphat Pugdeethosapol, Haowen Fang, Qinru Qiu
Grounding free-form textual queries necessitates an understanding of these textual phrases and its relation to the visual cues to reliably reason about the described locations.
no code implementations • 22 Mar 2020 • Ziyi Zhao, Zhao Jin, Wentian Bai, Wentan Bai, Carlos Caicedo, M. Cenk Gursoy, Qinru Qiu
In this paper, a deep learning-based UAS instantaneous density prediction model is presented.
no code implementations • 22 Mar 2020 • Ziyi Zhao, Haowen Fang, Zhao Jin, Qinru Qiu
The trajectory prediction is a critical and challenging problem in the design of an autonomous driving system.
2 code implementations • 19 Feb 2020 • Haowen Fang, Amar Shrestha, Ziyi Zhao, Qinru Qiu
A bio-plausible SNN model with spatial-temporal property is a complex dynamic system.
no code implementations • 11 Jan 2020 • Siyu Liao, Jie Chen, Yanzhi Wang, Qinru Qiu, Bo Yuan
Continuous representation of words is a standard component in deep learning-based NLP models.
no code implementations • 8 Jan 2020 • Amar Shrestha, Krittaphat Pugdeethosapol, Haowen Fang, Qinru Qiu
When the navigational environment is known, it can be represented as a graph where landmarks are nodes, the robot behaviors that move from node to node are edges, and the route is a set of behavioral instructions.
no code implementations • 28 Feb 2019 • Siyu Liao, Zhe Li, Liang Zhao, Qinru Qiu, Yanzhi Wang, Bo Yuan
Deep neural networks (DNNs), especially deep convolutional neural networks (CNNs), have emerged as the powerful technique in various machine learning applications.
no code implementations • 12 Dec 2018 • Zhe Li, Caiwen Ding, Siyue Wang, Wujie Wen, Youwei Zhuo, Chang Liu, Qinru Qiu, Wenyao Xu, Xue Lin, Xuehai Qian, Yanzhi Wang
It is a challenging task to have real-time, efficient, and accurate hardware RNN implementations because of the high sensitivity to imprecision accumulation and the requirement of special activation function implementations.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 10 May 2018 • Zhe Li, Ji Li, Ao Ren, Caiwen Ding, Jeffrey Draper, Qinru Qiu, Bo Yuan, Yanzhi Wang
Recently, Deep Convolutional Neural Network (DCNN) has achieved tremendous success in many machine learning applications.
no code implementations • 11 Apr 2018 • Ziyi Zhao, Krittaphat Pugdeethosapol, Sheng Lin, Zhe Li, Caiwen Ding, Yanzhi Wang, Qinru Qiu
The topic modeling discovers the latent topic probability of the given text documents.
no code implementations • 20 Mar 2018 • Zhe Li, Xiaolong Ma, Hongjia Li, Qiyuan An, Aditya Singh Rathore, Qinru Qiu, Wenyao Xu, Yanzhi Wang
It is of vital importance to enable 3D printers to identify the objects to be printed, so that the manufacturing procedure of an illegal weapon can be terminated at the early stage.
no code implementations • 20 Mar 2018 • Zhe Li, Shuo Wang, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Yun Liang
Recurrent Neural Networks (RNNs) are becoming increasingly important for time series-related applications which require efficient and real-time implementations.
no code implementations • 14 Mar 2018 • Shuo Wang, Zhe Li, Caiwen Ding, Bo Yuan, Yanzhi Wang, Qinru Qiu, Yun Liang
The previous work proposes to use a pruning based compression technique to reduce the model size and thus speedups the inference on FPGAs.
no code implementations • 18 Feb 2018 • Yanzhi Wang, Caiwen Ding, Zhe Li, Geng Yuan, Siyu Liao, Xiaolong Ma, Bo Yuan, Xuehai Qian, Jian Tang, Qinru Qiu, Xue Lin
Hardware accelerations of deep learning systems have been extensively investigated in industry and academia.
no code implementations • 29 Aug 2017 • Caiwen Ding, Siyu Liao, Yanzhi Wang, Zhe Li, Ning Liu, Youwei Zhuo, Chao Wang, Xuehai Qian, Yu Bai, Geng Yuan, Xiaolong Ma, Yi-Peng Zhang, Jian Tang, Qinru Qiu, Xue Lin, Bo Yuan
As the size of DNNs continues to grow, it is critical to improve the energy efficiency and performance while maintaining accuracy.
no code implementations • 13 Mar 2017 • Ning Liu, Zhe Li, Zhiyuan Xu, Jielong Xu, Sheng Lin, Qinru Qiu, Jian Tang, Yanzhi Wang
Automatic decision-making approaches, such as reinforcement learning (RL), have been applied to (partially) solve the resource allocation problem adaptively in the cloud computing system.
no code implementations • 12 Mar 2017 • Ji Li, Zihao Yuan, Zhe Li, Caiwen Ding, Ao Ren, Qinru Qiu, Jeffrey Draper, Yanzhi Wang
Recently, Deep Convolutional Neural Networks (DCNNs) have made unprecedented progress, achieving the accuracy close to, or even better than human-level perception in various tasks.
no code implementations • 18 Nov 2016 • Ao Ren, Ji Li, Zhe Li, Caiwen Ding, Xuehai Qian, Qinru Qiu, Bo Yuan, Yanzhi Wang
Stochastic Computing (SC), which uses bit-stream to represent a number within [-1, 1] by counting the number of ones in the bit-stream, has a high potential for implementing DCNNs with high scalability and ultra-low hardware footprint.