Do you know @Helve ?

Helve works with ambitious organisations to drive change through innovation, strategic partnerships and communication.

Say hi to Co-founder @marijarucevska! πŸ‘‹

Links πŸ‘‡πŸ‘‡πŸ‘‡ Image
They strive to cultivate the competitive advantage of Baltic enterprises by fostering our own and partner ventures in #innovation, #digitaltransformation, #sustainability, and #startup ecosystem collaboration.
Their sub-brands include Future Hub, open innovation accelerator solely focusing on sustainability.

The program brings together Baltic market-leading enterprises with top EU impact tech startups to facilitate partnerships for a 2-month co-creation process of a pilot project.
Helve
helve.eu

Future Hub
future-hub.eu

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More from @_IlirAliu

26 Nov
πŸ€“ StartupSpotter πŸ€“

They call themselves
β€˜creative bunch of data nerdsβ€˜

orchest.io
Build pipelines iteratively by editing and connecting notebooks and scripts.

@RickLamers and github.com/yannickperrenet πŸ‘‹
are the Co-Founders of this πŸ”₯ Startup!
Jupyter notebooks are a dominant tool for data scientists, but they lack a number of conveniences for building reusable and maintainable systems.
orchest.io

No frameworks. No YAML.
Just write your data processing code directly
in Python, R, Julia or Bash.
Read 7 tweets
26 Nov
Lidar with Velocity:
Motion Distortion Correction of Point Clouds
from Oscillating Scanning Lidars

In this paper, Gaussian-based lidar and camera fusion is proposed to estimate the full velocity and correct the lidar distortion. Image
Lidar point cloud distortion from moving object is an important problem in autonomous driving, and recently becomes even more demanding with the emerging of newer lidars, which feature back-and-forth scanning patterns.
Accurately estimating moving object velocity would not only provide a tracking capability but also correct the point cloud distortion with more accurate description of the moving object.
Read 7 tweets
25 Nov
Efficient and Robust
LiDAR-Based
End-to-End Navigation

Paper πŸ‘‡πŸ‘‡πŸ‘‡
Paper: arxiv.org/pdf/2105.09932
Credit: Zhijian Liu, Alexander Amini, Sibo Zhu, Sertac Karaman, Song Han, Daniela Rus
Deep learning has been used to demonstrate end-to-end neural network learning for autonomous vehicle control from raw sensory input.
Read 10 tweets
25 Nov
SimpleTrack:
Understanding and Rethinking
3D Multi-object Tracking

3D multi-object tracking (MOT) has witnessed numerous novel benchmarks and approaches in recent years, especially those under the "tracking-by-detection" paradigm. Image
Despite their progress and usefulness, an in-depth analysis of their strengths and weaknesses is not yet available.
In this paper, they summarize current 3D MOT methods into a unified framework by decomposing them into four constituent parts: pre-processing of detection, association, motion model, and life cycle management.
Read 8 tweets
25 Nov
Logistics is an industry which is infamous for being painfully opaque.

I have the pleasure to work together with @integrity Next.
integritynext.com

IN enables procurement organizations to qualify and monitor their suppliers.
- to improve sustainability and compliance, meet customer demands and regulatory requirements.
The challenge

Activities can be outsourced, but responsibility can not.
Read 6 tweets
24 Nov
✨StartupSpotter: SYNTROPY ✨

@Syntropynet is an open project
providing next-gen connectivity tech for the Internet.

It offers technology that is compatible with current internet infrastructure and its protocols
--> but introduces a crucial layer of programmability.
Founder:
William B. Norton @wbnorton
Dom Povilauskas @povilauskas
Jonas Simanavicius @JSimanavicius

Hi guys! πŸ‘‹
New Connectivity Layer for the Internet.

Establishing an open alternative data security and routing system, operating right on top of the existing Internet protocols. Image
Read 9 tweets

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