Name: Dipam Goswami
Type: User
Company: Computer Vision Center
Bio: PhD student at Computer Vision Center, Universitat Autonoma de Barcelona. M.Sc. Maths, B.E. CS from BITS Pilani, India.
Exploring Continual Learning.
Twitter: dipam_goswami
Location: Barcelona, Spain
Blog: sites.google.com/pilani.bits-pilani.ac.in/dipam-goswami/
Dipam Goswami's Projects
Code for CVPR 2024 paper - Resurrecting Old Classes with New Data for Exemplar-Free Continual Learning
ASM ASSIGNMENT 2 CODE
Awesome Incremental Learning
Official repository for our paper on "Attribution-aware Weight Transfer: A Warm-Start Initialization for Class-Incremental Semantic Segmentation" published at WACV 2023.
Bounding Box Priors for Cell Detection with Point Annotations
Data Analysis on Big mart sales data
Billing Management System Layout using Template
Video action classification on the Breakfast actions dataset.
Applying Convolutional Neural Networks to MNIST Dataset
Official code of CVPR 2021's PLOP: Learning without Forgetting for Continual Semantic Segmentation
Python implementation of the Eliza chatbot
Eliza-Android is an Android implementation of the popular chatterbot created by Joseph Weizenbaum.
To maintain a register of employees
Framework for Analysis of Class-Incremental Learning with 12 state-of-the-art methods and 3 baselines.
Code for NeurIPS 2023 paper - FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning
Code for CLVision workshop (CVPR 2024) paper - Calibrating Higher-Order Statistics for Few-Shot Class-Incremental Learning with Pre-trained Vision Transformers
Computing Gradient Descent for a sample data
Image Processing on Rectangular Layouts using Matlab
A collection of incremental learning paper implementations including PODNet (ECCV20) and Ghost (CVPR-W21).
Keras implementation of RetinaNet object detection.
Monocular depth estimation from a single image
Different Applications of Natural Language Processing using TensorFlow
This contains the basics of neural networks and deep learning
Principal Component Analysis with sklearn