![Frontiers | An efficient tomato-detection method based on improved YOLOv4-tiny model in complex environment Frontiers | An efficient tomato-detection method based on improved YOLOv4-tiny model in complex environment](https://www.frontiersin.org/files/Articles/1150958/fpls-14-1150958-HTML/image_m/fpls-14-1150958-g001.jpg)
Frontiers | An efficient tomato-detection method based on improved YOLOv4-tiny model in complex environment
![Drones | Free Full-Text | Research on Object Detection and Recognition Method for UAV Aerial Images Based on Improved YOLOv5 Drones | Free Full-Text | Research on Object Detection and Recognition Method for UAV Aerial Images Based on Improved YOLOv5](https://www.mdpi.com/drones/drones-07-00402/article_deploy/html/images/drones-07-00402-g001.png)
Drones | Free Full-Text | Research on Object Detection and Recognition Method for UAV Aerial Images Based on Improved YOLOv5
![Applied Sciences | Free Full-Text | Deep Learning Based Detector YOLOv5 for Identifying Insect Pests Applied Sciences | Free Full-Text | Deep Learning Based Detector YOLOv5 for Identifying Insect Pests](https://www.mdpi.com/applsci/applsci-12-10167/article_deploy/html/images/applsci-12-10167-g001.png)
Applied Sciences | Free Full-Text | Deep Learning Based Detector YOLOv5 for Identifying Insect Pests
![Frontiers | Comparing Object Recognition in Humans and Deep Convolutional Neural Networks—An Eye Tracking Study Frontiers | Comparing Object Recognition in Humans and Deep Convolutional Neural Networks—An Eye Tracking Study](https://www.frontiersin.org/files/Articles/750639/fnins-15-750639-HTML/image_m/fnins-15-750639-g001.jpg)
Frontiers | Comparing Object Recognition in Humans and Deep Convolutional Neural Networks—An Eye Tracking Study
![Deep learning in computer vision: A critical review of emerging techniques and application scenarios - ScienceDirect Deep learning in computer vision: A critical review of emerging techniques and application scenarios - ScienceDirect](https://ars.els-cdn.com/content/image/1-s2.0-S2666827021000670-gr2.jpg)