An AI made using artificial intelligence (AI) and machine learning algorithms (ML) .

Last update: Jan 06, 2022

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Overview

DTech.AIML

An AI made using artificial intelligence (AI) and machine learning algorithms (ML) . This is created by help of some members in my team and they have a vast big contribution in this project.

Any way welcome to the DTech which stands for Darshan Technologies here we are creating projects using AI artificial intelligence and ML that is machine learning algorithms. Recently we have made a stock market value predicting model and this very profitable in all the case .

Any way hope that if you are reading this documentation to the end then we hope that you will be Stay forever with us helping in builting new project and to get new project ideas.

Team Members :::--->>> ______________________: 1)Darshan 2)Shubham 3)Arijit

Owner

GitHub Repository

Clairvoyance: a Unified, End-to-End AutoML Pipeline for Medical Time Series

Clairvoyance: A Pipeline Toolkit for Medical Time Series Authors: van der Schaar Lab This repository contains implementations of Clairvoyance: A Pipel

$van_der_Schaar \LAB$ 89 Dec 07, 2022

Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation (ACM MM 2020)

Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation (ACM MM 2020) Official implementation of: Forest R-CNN: Large-Vo

54 Jan 06, 2023

Rethinking Transformer-based Set Prediction for Object Detection

Rethinking Transformer-based Set Prediction for Object Detection Here are the code for the ICCV paper. The code is adapted from Detectron2 and AdelaiD

62 Dec 03, 2022

[CVPR 2021] 'Searching by Generating: Flexible and Efficient One-Shot NAS with Architecture Generator'

[CVPR2021] Searching by Generating: Flexible and Efficient One-Shot NAS with Architecture Generator Overview This is the entire codebase for the paper

35 Dec 01, 2022

Code for the paper "Learning-Augmented Algorithms for Online Steiner Tree"

Learning-Augmented Algorithms for Online Steiner Tree This is the code for the paper "Learning-Augmented Algorithms for Online Steiner Tree". Requirem

0 Dec 09, 2021

Double pendulum simulator using a symplectic Euler's method and Hamiltonian mechanics

Symplectic Double Pendulum Simulator Double pendulum simulator using a symplectic Euler's method. The program calculates the momentum and position of

1 Jan 12, 2022

Official implementation of Unfolded Deep Kernel Estimation for Blind Image Super-resolution.

Unfolded Deep Kernel Estimation for Blind Image Super-resolution Hongyi Zheng, Hongwei Yong, Lei Zhang, "Unfolded Deep Kernel Estimation for Blind Ima

15 Dec 26, 2022

Industrial Image Anomaly Localization Based on Gaussian Clustering of Pre-trained Feature

Industrial Image Anomaly Localization Based on Gaussian Clustering of Pre-trained Feature Q. Wan, L. Gao, X. Li and L. Wen, "Industrial Image Anomaly

6 Dec 25, 2022

YuNetのPythonでのONNX、TensorFlow-Lite推論サンプル

YuNet-ONNX-TFLite-Sample YuNetのPythonでのONNX、TensorFlow-Lite推論サンプルです。 TensorFlow-LiteモデルはPINTO0309/PINTO_model_zoo/144_YuNetのものを使用しています。 Requirement Op

8 Nov 17, 2021

YOLTv4 builds upon YOLT and SIMRDWN, and updates these frameworks to use the most performant version of YOLO, YOLOv4

YOLTv4 builds upon YOLT and SIMRDWN, and updates these frameworks to use the most performant version of YOLO, YOLOv4. YOLTv4 is designed to detect objects in aerial or satellite imagery in arbitraril

161 Jan 06, 2023

Direct design of biquad filter cascades with deep learning by sampling random polynomials.

IIRNet Direct design of biquad filter cascades with deep learning by sampling random polynomials. Usage git clone https://github.com/csteinmetz1/IIRNe

55 Nov 02, 2022

Tensorflow Repo for "DeepGCNs: Can GCNs Go as Deep as CNNs?"

DeepGCNs: Can GCNs Go as Deep as CNNs? In this work, we present new ways to successfully train very deep GCNs. We borrow concepts from CNNs, mainly re

612 Nov 15, 2022

This is official implementaion of paper "Token Shift Transformer for Video Classification".

This is official implementaion of paper "Token Shift Transformer for Video Classification". We achieve SOTA performance 80.40% on Kinetics-400 val. Paper link

60 Dec 30, 2022

Baselines for TrajNet++

TrajNet++ : The Trajectory Forecasting Framework PyTorch implementation of Human Trajectory Forecasting in Crowds: A Deep Learning Perspective TrajNet

183 Jan 05, 2023

This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEECH" submitted to ICASSP 2022

CPC_DeepCluster This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEEC

2 Sep 15, 2022