Taoseef Ishtiak's repositories
MyPytorchWork
The repository contains the implementation of the basic algorithms: Linear Regression, Customized ANN, Gradient Descent, CNN for classification, NLP, RNN, and Time Series Analysis. with some of the well-known datasets found on the web.
ArduinoProjects
This repository contains the code of the Arduino projects that I worked on during my BS degree completion.
biomedicalImageSegmentationNSU
The repository contains the reproduction of UNetPluPlus, introduced by Z. Zhou, M. M. R. Siddiquee, N. Tajbakhsh, and J. Liang; upon the dataset obtained from the KITS19 Kidney Tumor Segmentation Challenge.
CSE327Team95
This repository contains the dedicated work of my CSE327: Software Engineering term project. It is a FB App Clone Web Application. I along with 3 of my group mates are developing the project.
EMOST
This repository contains the software development work done during my research work of an algorithm development for reducing household electricity consumption with respect to weather information using REST API and sending data to server automatically. The software development had been done basically to build a Web Application suggesting for reducing electricity consumption with maven and JavaFX
NSUEnvDeptProject1
The repository contains my back end android and web app development work for the project Coastal Area Data Collection for Vulnerability Assessment and analyzing Machine Learning Approaches. It was a Govt. funded research, jointly supervised by the Department of Environment, Government of People’s Republic of Bangladesh and Department of Environmental Science and Management, North South University. I worked as a back end developer for building an android application for data collection and a web platform to project the data and crucial information running SQL queries. The other contributor worked in Front end development. In another part of the project, I was given the responsibility for dimensionality reduction of vulnerability assessment. Based on a partial dataset I applied Backward elimination, L1 Based Feature Selection and Low Variance Feature Removal techniques to analyse the feature selection process. This project has been nominated to be used on a massive scale to gather non private data of coastal areas’ people to improve their lives styles and disaster vulnerability assessment. I am currently working as a technical advisor in the project.
caffe-segnet
Implementation of SegNet: A Deep Convolutional Encoder-Decoder Architecture for Semantic Pixel-Wise Labelling
Custom-Object-Detection
Custom Object Detection with TensorFlow
image-segmentation-keras
Implementation of Segnet, FCN, UNet , PSPNet and other models in Keras.
labelImg
:metal: LabelImg is a graphical image annotation tool and label object bounding boxes in images
Mask_RCNN
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
raccoon_dataset
The dataset is used to train my own raccoon detector and I blogged about it on Medium
Real-Time-Facial-Expression-Recognition
A Deep Learning Case Study to detect one of the Seven Human Facial Expressions in Still Images and in Real Time. This model is also trained enough to Detect Facial Expressions of Animated Images.
training-data-analyst
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
uber-tlc-foil-response
Uber trip data from a freedom of information request to NYC's Taxi & Limousine Commission