Detect and Recognize Mines and IEDs hidden in the environment
Sector: Advanced Electronics • Location: Poland, France, Austria, Estonia, Netherlands
Source: EU Funding & Tenders Portal
The DeterMine (Detect and Recognize Mines and IEDs hidden in the environment) project is targeted to generate knowledge and to contribute to the strengthening of the EU knowledgebase and creation of the standardised benchmarks for evaluation of the landmine and IEDs detection systems, to ultimately pave the way for enhanced protection of personnel and infrastructures and freedom of actions for mil
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | ongoing |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | The DeterMine (Detect and Recognize Mines and IEDs hidden in the environment) project is targeted to generate knowledge and to contribute to the strengthening of the EU knowledgebase and creation of the standardised benchmarks for evaluation of the landmine and IEDs detection systems, to ultimately pave the way for enhanced protection of personnel and infrastructures and freedom of actions for military forces. DeterMine aims to achieve this goal by using the technological challenge to verify the concept for a modular multisensory and multiplatform solution for hidden threats detection and identification, gathering and sharing data from the test fields and working on data improvement by applying AI and data fusion techniques, pursuing as an overall objective the improvement of the major metrics: detection accuracy and hidden threat classification and feature estimation. The project is driven by an incremental approach allowing to test different technologies, sensor combinations and data fusion algorithms. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
Project Type | Obfuscated Data |
Article Published Date | Obfuscated Data |
