Sandipan Sarma (sandipan211)

sandipan211

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Company:Indian Institute of Technology Guwahati

Location:Guwahati, Assam, India

Twitter:@sandipan_7

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Sandipan Sarma's repositories

ZSD-SC-Resolver

Resolving semantic confusions for improved zero-shot detection (BMVC 2022)

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Coding-assignments

Coding assignments done during B.Tech (2015-2019) at IIEST, Shibpur, and during Ph.D. at IIT Guwahati (2019-present)

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InvPT

Code of ECCV2022 paper "Inverted Pyramid Multi-task Transformer for Dense Scene Understanding"

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A_Guide_to_Running_Tensorflow_Models_on_Android

This is the code for"A Guide to Running Tensorflow Models on Android" By SIraj Raval on Youtube

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anonymous_github

Anonymous Github is a proxy server to support anonymous browsing of Github repositories for open-science code and data.

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Automatic-handgun-detection

Auto. handgun detection in images is done using SVM classifier and SIFT feature extractor and compared with the existing Faster R-CNN object detector

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CompetitiveProgramming

A collection of algorithms, data structures and other useful information for competitive programming.

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K-nearest-neighbor-algorithm-modification

tried modifications of this algorithm in new domains

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tensorflow_cookbook

Code for Tensorflow Machine Learning Cookbook

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awesome-object-detection

Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html

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Codes-for-Common-Data-Structures-and-Algorithms

Codes for common DSA - all in one

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deep-learning

Deep Learning Application Examples

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DiRaC-I

Intelligent algorithm for selecting suitable training classes for zero-shot object recognition that capture domain diversity and rarity

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DL-templates

Contains template codes of various deep learning models

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OpenHmnD

Your True Open-Source Humanoid

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pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

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t81_558_deep_learning

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

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VideoX

VideoX: a collection of video cross-modal models

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