jiankangren

-REAL-TIME-VEHICLE-CLASSIFICATION-AND-LOCALIZATION-USING-EDGE-COMPUTING-

The project aims to develop a traffic monitoring system using convolution neural network. We had modified existing tiny YOLO model for Indian vehicle such as auto rickshaw, bicycle, motorbikes etc. To do this, first we developed a data set of these vehicles then we retrained the existing tiny YOLO model. Moreover, with raspberry Pi we have developed a prototype for edge device which can count incoming and outgoing traffic from a particular point. There are various applications of such devices for example, it can be used as traffic monitoring system, surveillance, traffic load prediction. This is a fully functional independent device. All the decision has been done locally, this make this device highly useful for IoTs.

2018-DAC-System-Design-Contest

4ceedframework

Real-time Acquisition and Analysis Framework for Materials-related Cyber-Physical Environments

Abnormal-Behavior-Detection-Based-On-Optical-Flow-Features

CSC2515-University of Toronto. This project applied computer vision and mechine learning methods aimed to detect abnormal behaved object in crowd, by Hanwen Liang and Haohan Li.

abstract-value-iteration

Code for experiments in the paper "Abstract Value Iteration for Hierarchical Reinforcement Learning" (https://arxiv.org/abs/2010.15638)

CL-Embedding-CNN

Character-level Embedding with Convolutional Neural Network for Malicious Web Request Detection

Hierarchical-Fuzzy-Tree

Software: The Hierarchical Fuzzy Inference Tree Software Toolbox is a function approximation and feature selection tool that uses genetic programming for constructing tree like structure to construct an adaptive multi-layer perceptron. This standalone software toolbox solves prediction problems. The developed algorithm performs multiobjective in which it adaptively creates a simple models with high generalization ability.

online-mec

Validation for an online resource allocation algorithm for mobile edge computing

Quantum_Computation

量子计算相关学习

Simulation_MEC

Implementing and applying offloading algorithms on simulation-based MEC.

jiankangren/DATE_2020

Contains the cleaned up code of DATE 2020

jiankangren/PyCLiPSM

PyCLiPSM - Harnessing Heterogeneous Computing Resources on CPUs and GPUs for Accelerated Digital Soil Mapping

jiankangren/ASPDAC_2019

jiankangren/FANET

Flying Ad-Hoc Network

jiankangren/multicore-simulator

A Computers Architecture project. Consist in the simulation of a multicore processor. To handle cache coherence and operations related to memory read and write

jiankangren/SCALE-Sim

jiankangren/clang

jiankangren/openmp

jiankangren/llvm

jiankangren/m2s-cgm

A detailed architectural simulator for heterogeneous CPU-GPU systems

jiankangren/eyeriss_v1

jiankangren/np-schedulability-analysis

An implementation of schedulability tests for non-preemptive job sets, for uni- and global multiprocessors, with precedence constraints.

jiankangren/People-Counting-Crowd-Density-Detection

Project at #sg_wonder_vision study group of the Facebook Secure and Private AI Scholarship Challenge 2019

jiankangren/heft-1

HEFT Algorithm

jiankangren/RT-Gang

Real-Time Gang Scheduling in Linux

jiankangren/indices

jiankangren/litmus-rt

The LITMUS^RT kernel.

jiankangren/AdaptiveRoutingUsingRL

Code accompanying our submission to RTSS 2019 titled " Adaptive Routing with Guaranteed Delay Bounds using Safe Reinforcement Learning"

jiankangren/MC-DAG

Mixed-Criticality DAG Framework

jiankangren/Tensorflow-TensorRT

This repository is for my YT video series about optimizing a Tensorflow deep learning model using TensorRT. We demonstrate optimizing LeNet-like model and YOLOv3 model, and get 3.7x and 1.5x faster for the former and the latter, respectively, compared to the original models.

jiankangren/VisDrone2018-MOT-toolkit

Multiple Object Tracking toolkit for VisDrone2019

jiankangren/CornerNet-Lite-for-DAC2019-Yang

jiankangren/wcet-benchmarks

Modified Mälardalen WCET benchmarks, annoted with instruction timing

jiankangren/fpncc

Feature Pyramid Networks for Crowd Counting (FPNCC)

jiankangren/Multi-Camera-Object-Tracking-via-Transferring-Representation-to-Top-View

Multi-Camera Object Tracking via Deep Metric Learning

jiankangren/posix_quic

Posix style QUIC protocol.

jiankangren/SMART-ECRTS19

Code and data for the ECRTS'19 submission of Sims H. Osborne, Joshua J. Bakita, and James H. Anderson

jiankangren/Classification_Based_Reachability

Vicenç Rubies Royo, David Fridovich-Keil, Sylvia Herbert, and Claire J. Tomlin, "Classification-based Approximate Reachability with Guarantees Applied to Safe Trajectory Tracking." IEEE International Conference on Intelligent Robots, 2019

jiankangren/ros2_response_time_analysis

Supplementary source code for the ECRTS 2019 paper 'Response-Time Analysis of ROS 2 Processing Chains under Reservation-Based Scheduling'

jiankangren/drone-swarm

Simulation of swarm behaviour