Follow the Soldiers with Optimized Single-Shot Multibox Detection and Reinforcement Learning

2023-08-02 · Jumman Hossain, Maliha Momtaz

Nowadays, autonomous cars are gaining traction due to their numerous potential applications on battlefields and in resolving a variety of other real-world challenges. The main goal of our project is to build an autonomous system using DeepRacer which will follow a specific person (for our project, a soldier) when they will be moving in any direction. Two main components to accomplish this project is an optimized Single-Shot Multibox Detection (SSD) object detection model and a Reinforcement Learning (RL) model. We accomplished the task using SSD Lite instead of SSD and at the end, compared the results among SSD, SSD with Neural Computing Stick (NCS), and SSD Lite. Experimental results show that SSD Lite gives better performance among these three techniques and exhibits a considerable boost in inference speed (~2-3 times) without compromising accuracy.

📄 PDF Abstract BibTeX arXiv:2308.01389

Code (0)

등록된 구현이 없습니다.

Tasks

object-detection Object Detection reinforcement-learning Reinforcement Learning (RL)

Methods 이 논문이 사용한 방법론

1x1 Convolution A 1 x 1 Convolution is a convolution with some special properties in that it can be used for dimensionality reduction,…

Non Maximum Suppression Non Maximum Suppression is a computer vision method that selects a single entity out of many overlapping entities (for example bounding boxes in object detection). The…

Convolution A convolution is a type of matrix operation, consisting of a kernel, a small matrix of weights, that slides over input data performing element-wise multiplication with the…

SSD SSD is a single-stage object detection method that discretizes the output space of bounding boxes into a set of default boxes over different aspect ratios and scales per…

SPEED The monocular depth estimation (MDE) is the task of estimating depth from a single frame. This information is an essential knowledge in many computer vision tasks such as scene…

FSSD: Feature Fusion Single Shot Multibox Detector

2017-12-04 · Zuoxin Li, Lu Yang, Fuqiang Zhou

SSD (Single Shot Multibox Detector) is one of the best object detection algorithms with both high accuracy and fast speed. However, SSD's feature pyramid detection method makes it hard to fuse the features from different…

GPU object-detection Object Detection

Applying the Wizard-of-Oz Technique to Multimodal Human-Robot Dialogue

2017-03-10 · Matthew Marge, Claire Bonial, Brendan Byrne, Taylor Cassidy 외

Our overall program objective is to provide more natural ways for soldiers to interact and communicate with robots, much like how soldiers communicate with other soldiers today. We describe how the Wizard-of-Oz (WOz) met…

Dialogue Management Management Robot Navigation

CvT-ASSD: Convolutional vision-Transformer Based Attentive Single Shot MultiBox Detector

2021-10-24 · Weiqiang Jin, Hang Yu

Due to the success of Bidirectional Encoder Representations from Transformers (BERT) in natural language process (NLP), the multi-head attention transformer has been more and more prevalent in computer-vision researches …

Computational Efficiency Novel Object Detection object-detection Object Detection+1

Extend the shallow part of Single Shot MultiBox Detector via Convolutional Neural Network

2018-01-18 · Liwen Zheng, Canmiao Fu, Yong Zhao

Single Shot MultiBox Detector (SSD) is one of the fastest algorithms in the current object detection field, which uses fully convolutional neural network to detect all scaled objects in an image. Deconvolutional Single S…

GPU object-detection Object Detection

Detecting Small Objects in Thermal Images Using Single-Shot Detector

2021-08-25 · Hao Zhang, Xianggong Hong, Li Zhu

SSD (Single Shot Multibox Detector) is one of the most successful object detectors for its high accuracy and fast speed. However, the features from shallow layer (mainly Conv4_3) of SSD lack semantic information, resulti…

GPU Object object-detection Object Detection+1