# Investigating the Efficiency of Deep Learning Models in Bioinspired Object Detection

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/investigating-the-efficiency-of-deep-learning-models-in-bioinspired-object/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Sunday Adeola Ajagbe,Olukayode Oki,Matthew Abiola Oladipupo,Andrew Chinonso Nwanakwaugwu |
| Citations | 30 |
| DOI | 10.1109/icecet55527.2022.9872568 |
| Fields | Agricultural and Biological Sciences,Computer Science,Engineering |
| Open Access | true |
| OA Status | green |
| OA URL | http://usir.salford.ac.uk/id/eprint/65025/ |
| OpenAlex ID | https://openalex.org/W4295036733 |
| Type | conference-paper |
| Year | 2022 |

## Paper authors

- [Matthew Abiola Oladipupo](https://scholariq.org/researchers/matthew-abiola-oladipupo/)

## Paper journal

- [2022 International Conference on Electrical, Computer and Energy Technologies (ICECET)](https://scholariq.org/journals/2022-international-conference-on-electrical-computer-and-energy-technologies/)

## Paper primary topic

- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)

## Paper topics

- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)
- [Industrial Vision Systems and Defect Detection](https://scholariq.org/topics/industrial-vision-systems-and-defect-detection/)
- [Smart Agriculture and AI](https://scholariq.org/topics/smart-agriculture-and-ai/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.