Mechanism for Visual Detection of Small Targets in Insects

2013 ◽  
Author(s):  
David C. O'Carroll ◽  
Steven D. Wiederman ◽  
Patrick A. Shoemaker
Keyword(s):  
Visual Detection ◽  
Small Targets

scholarly journals Ship Target Detection Algorithm Based on Improved YOLOv5

2021 ◽  
Vol 9 (8) ◽  
pp. 908
Author(s):  
Junchi Zhou ◽  
Ping Jiang ◽  
Airu Zou ◽  
Xinglin Chen ◽  
Wenwu Hu
Keyword(s):  
Visual Detection ◽  
Detection System ◽  
Recall Rate ◽  
Detection Algorithm ◽  
Average Precision ◽  
Fast Detection ◽  
Detection And Identification ◽  
Small Targets ◽  
Improved Model ◽  
Field Area

In order to realize the real-time detection of an unmanned fishing speedboat near a ship ahead, a perception platform based on a target visual detection system was established. By controlling the depth and width of the model to analyze and compare training, it was found that the 5S model had a fast detection speed but low accuracy, which was judged to be insufficient for detecting small targets. In this regard, this study improved the YOLOv5s algorithm, in which the initial frame of the target is re-clustered by K-means at the data input end, the receptive field area is expanded at the output end, and the loss function is optimized. The results show that the precision of the improved model’s detection for ship images was 98.0%, and the recall rate was 96.2%. Mean average precision (mAP) reached 98.6%, an increase of 4.4% compared to before the improvements, which shows that the improved model can realize the detection and identification of multiple types of ships, laying the foundation for subsequent path planning and automatic obstacle avoidance of unmanned ships.

scholarly journals TF-YOLO: An Improved Incremental Network for Real-Time Object Detection

2019 ◽  
Vol 9 (16) ◽  
pp. 3225 ◽  
Author(s):  
He ◽  
Huang ◽  
Wei ◽  
Li ◽  
Guo
Keyword(s):  
Embedded System ◽  
Object Detection ◽  
Real Time ◽  
Visual Detection ◽  
Portable Devices ◽  
Detection Model ◽  
Multi Scale ◽  
Art Object ◽  
Feature Pyramid ◽  
Small Targets

In recent years, significant advances have been gained in visual detection, and an abundance of outstanding models have been proposed. However, state-of-the-art object detection networks have some inefficiencies in detecting small targets. They commonly fail to run on portable devices or embedded systems due to their high complexity. In this workpaper, a real-time object detection model, termed as Tiny Fast You Only Look Once (TF-YOLO), is developed to implement in an embedded system. Firstly, the k-means++ algorithm is applied to cluster the dataset, which contributes to more excellent priori boxes of the targets. Secondly, inspired by the multi-scale prediction idea in the Feature Pyramid Networks (FPN) algorithm, the framework in YOLOv3 is effectively improved and optimized, by three scales to detect the earlier extracted features. In this way, the modified network is sensitive for small targets. Experimental results demonstrate that the proposed TF-YOLO method is a smaller, faster and more efficient network model increasing the performance of end-to-end training and real-time object detection for a variety of devices.

Anxious anticipation prolongs emotional interference for rapid visual detection.

Emotion ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1127-1137
Author(s):  
Nadia Haddara ◽  
Jonathan Ravid ◽  
Erica L. Miller ◽  
Molly O'Hagan ◽  
Chris Caracciolo ◽  
...  
Keyword(s):  
Visual Detection ◽  
Emotional Interference

Use of hybrid shots in planning Perfexion Gamma Knife treatments for lesions close to critical structures

2008 ◽  
Vol 109 (Supplement) ◽  
pp. 34-40 ◽  
Author(s):  
Paula L. Petti ◽  
David A. Larson ◽  
Sandeep Kunwar
Keyword(s):  
Optic Nerve ◽  
Gamma Knife ◽  
Pituitary Tumor ◽  
Metastatic Lesion ◽  
Conformity Index ◽  
Target Coverage ◽  
Critical Areas ◽  
Planning Technique ◽  
Small Targets ◽  
Critical Structure

Object The authors investigated the use of different collimator values in different sectors (hybrid shots) when treating patients with lesions close to critical structures with the Perfexion model Gamma Knife. Methods Twelve patients with various tumors (6 with a pituitary tumor, 3 with vestibular schwannoma, 2 with meningioma, and 1 with metastatic lesion) that were within 4 mm of the brainstem, optic nerve, pituitary stalk, or cochlea were considered. All patients were treated at the authors' institution between June 2007 and March 2008. The patients' treatments were replanned in 2 different ways. In the first plan, hybrid shots were used such that the steepest dose gradient was aligned with the junction between the target and the critical structure(s). This was accomplished by placing low-value collimators in appropriate sectors. In the second plan, no hybrid shots were used. Sector blocking (either manual or dynamic) was required for all plans to reduce the critical structure doses to acceptable levels. Prescribed doses ranged from 12 to 30 Gy at the periphery of the target. The plans in each pair were designed to be equally conformal in terms of both target coverage (as measured by the Paddick conformity index) and critical structure sparing. Results The average number of shots required was roughly the same using either planning technique (16.7 vs 16.6 shots with and without hybrids). However, for all patients, the number of blocked sectors required to protect critical areas was larger when hybrid shots were not used. On average, nearly twice as many blocked sectors (14.8 vs 7.0) were required for the plans that did not use hybrid shots. The number of high-value collimators used in each plan was also evaluated. For small targets (≤ 1 cm3), for which 8 mm was considered a high value for the collimator, plans employing hybrids used an average of 2.3 times as many 8-mm sectors as did their nonhybrid counterparts (7.4 vs 3.2 sectors). For large targets (> 1 cm3), for which 16 mm was considered a high value for the collimator, hybrid plans used an average of 1.4 times as many 16-mm sectors as did the plans without hybrids (10.7 vs 7.7 sectors). Decreasing the number of blocked sectors and increasing the number of high-value collimator sectors led to use of shorter beam-on times. Beam-on times were 1–39% higher (average 17%) when hybrid shots were not allowed. The average beam-on time for plans with and without hybrid shots was 67.4 versus 78.4 minutes. Conclusions The judicious use of hybrid shots in patients for whom the target is close to a critical structure is an efficient way to achieve conformal treatments while minimizing the beam-on time. The reduction in beam-on time with hybrid shots is attributed to a reduced use of blocked sectors and an increased number of high-value collimator sectors.

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