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android-social-network-app

A basic social networking app which allows users to post images and text and comment on posts. The app was made in Android and was done as a part of an assignment in DataBase Systems Lab

angular-flask

An AngularJS (frontend) + Flask / Python (backend) Boilerplate Application

awesome-competitive-programming

:gem: A curated list of awesome Competitive Programming, Algorithm and Data Structure resources

basic-language-parser

Parsing a string to extract the following elements: number, identifier, variable, term, expression and assignment

ble-packet-sniffer

An android application which is useful in capturing BLE advertisement packets and storing the data collected in the phone storage as a csv file.

bookbench

CS387 project

c3d_feature_extraction

C3D video feature extraction using Google Colab - Colaboratory.

census-income

Task is to predict whether income exceeds $50K/yr based on census data by implementing a Neural Network from Scratch

chat-application-optichat

A simple Chat Application using Socket Programming in Python.

dip-assignment-cs-663

Contains all the assignments related to Digital Image Processing

edge-intelligence

随着移动云计算和边缘计算的快速发展，以及人工智能的广泛应用，产生了边缘智能(Edge Intelligence)的概念。深度神经网络(例如CNN)已被广泛应用于移动智能应用程序中，但是移动设备有限的存储和计算资源无法满足深度神经网络计算的需求。神经网络压缩与加速技术可以加速神经网络的计算，例如剪枝、量化、卷积核分解等。但是这些技术在实际应用非常复杂，并且可能导致模型精度的下降。在移动云计算或边缘计算中，任务卸载技术可以突破移动终端的资源限制，减轻移动设备的计算负载并提高任务处理效率。通过任务卸载技术优化深度神经网络成为边缘智能研究中的新方向。Neurosurgeon: Collaborative Intelligence Between the Cloud and Mobile Edge这篇文章提出了协同推断的**，将深度神经网络进行分区，一部分层在移动端计算，而另一部分在云端计算。根据硬件平台、无线网络以及服务器负载等因素实现动态分区，降低时延以及能耗。本项目给出了边缘智能方面的相关论文，并且给出了一个Python语言实现的卷积神经网络协同推断实验平台。关键词：边缘智能(Edge Intelligence)，计算卸载(Computing Offloading)，CNN模型分区(CNN Partition)，协同推断(Collaborative Inference)，移动云计算(Mobile Cloud Computing)

fractals

Drawing Different types of fractals using Dr. Racket

gravity-simulation

Simulating Gravity among particles by approximating the forces between the particles using trees containing centre of masses of groups of particles

housing_values_in_suburbs_of_boston

Predicting the Housing values using Regression

human-activity-recognition

Classifying the physical activities performed by a user based on accelerometer and gyroscope sensor data collected by a smartphone in the user’s pocket. The activities to be classified are: Standing, Sitting, Stairsup, StairsDown, Walking and Cycling.

image-quilting-and-texture-synthesis

Digital Image Processing Course Project - IIT Bombay Fall 2018

imageseg-kmeans

💠 Image Segmentation using K-Means

ip-address-lookup-using-tries

Sequential IP address lookup in the routing table of routers has complexity O(n). This lookup can be reduced to O(1) time complexity, trading of with the space complexity which can be exponential in the worst case i.e. exp(2,33) - 1 on implementing tries.

mlops_videoanomalydetection

Operationalize a video anomaly detection model with Azure ML

mosh

Coding MoSh: 'My own Shell!'.

netvlad-pytorch

PyTorch implementation of NetVLAD & Online Hardest Triplet Loss.

pcube

pcube-icnp2018

Code for RnD project at IIT Bombay. This work was published at IEEE ICNP 2018 workshop P4EU.

ping-pong

A two player Ping Pong game using the '2htdp/universe' library in Racket

ply-compiler

Compiler written in ply

realtime-action-recognition

Contains code for C3D, LCN and TSM for action recognition models.

rssi-based-localization-using-esp32

Wireless Networks [CS 743] Course Project - IIT Bombay Spring 2019

safe-rl-pacman

Reinforcement Learning Course Project - IIT Bombay Fall 2018

spanning-tree-protocol

Implemented Spanning tree protocol and Learning Bridge algorithm in C++